An Indexed Bibliography of Genetic Algorithms and Neural Networks compiled by Jarmo T. Alander Department of Electrical and Energy Engineering: Automation University of Vaasa P.O. Box 700, FIN-65101 Vaasa, Finland phone: +358-6-324 8444, fax: +358-6-324 8467 dedicated to Teuvo Kohonen Report Series No. 94-1-NN (Updated 2012/06/28 09:52 ) available at http://lipas.uwasa.fi/~TAU/reports/report94-1/NNbib.pdf c 1994-2012 Jarmo T. Alander Copyright Trademarks Product and company names listed are trademarks or trade names of their respective companies. Warning While this bibliography has been compiled with the utmost care, the editor takes no responsibility for any errors, missing information, the contents or quality of the references, nor for the usefulness and/or the consequences of their application. The fact that a reference is included in this publication does not imply a recommendation. The use of any of the methods in the references is entirely at the user’s own responsibility. Especially the above warning applies to those references that are marked by trailing ’†’ (or ’*’), which are the ones that the editor has unfortunately not had the opportunity to read. An abstract was available of the references marked with ’*’. Contents 1 Preface 1.1 Your contributions erroneous or missing? 1.1.1 How to cite this report? . . . . . . 1.2 How to get this report via Internet? . . 1.3 Acknowledgement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Introduction 1 2 2 2 2 4 3 Statistical summaries 3.1 Publication type . . . . . 3.2 Annual distribution . . . . 3.3 Classification . . . . . . . 3.4 Authors . . . . . . . . . . 3.5 Geographical distribution 3.6 Conclusions and future . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 5 5 6 6 8 8 4 Indexes 4.1 Books . . . . . . . . . 4.2 Journal articles . . . . 4.3 Theses . . . . . . . . . 4.3.1 PhD theses . . 4.3.2 Master’s theses 4.4 Report series . . . . . 4.5 Patents . . . . . . . . 4.6 Authors . . . . . . . . 4.7 Subject index . . . . . 4.8 Annual index . . . . . 4.9 Geographical index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 9 9 14 14 14 14 15 17 43 57 59 . . . . . . . . . . . . . . . . . . . . . . Bibliography 61 Appendixes 171 A Bibliography entry formats 171 i ii Chapter 1 Preface “ Living organism are consummate problem solvers. They exhibit a versatility that puts the best computer programs to shame. ” John H. Holland, [1] The material of this bibliography has been extracted from the genetic algorithm bibliography [2], which when this report was compiled (June 28, 2012) contained 21690 items and which has been collected from several sources of genetic algorithm literature including Usenet newsgroup comp.ai.genetic and the bibliographies [3, 4, 5, 6]. The following index periodicals and databases have been used systematically • A: International Aerospace Abstracts: Jan. 1995 – Sep. 1998 • ACM: ACM Guide to Computing Literature: 1979 – 1993/4 • BA: Biological Abstracts: July 1996 - Aug. 1998 • CA: Computer Abstracts: Jan. 1993 – Feb. 1995 • CCA: Computer & Control Abstracts: Jan. 1992 – Dec. 1999 (except May -95) • ChA: Chemical Abstracts: Jan. 1997 - Dec. 2000 • CTI: Current Technology Index Jan./Feb. 1993 – Jan./Feb. 1994 • DAI: Dissertation Abstracts International: Vol. 53 No. 1 – Vol. 56 No. 10 (Apr. 1996) • EEA: Electrical & Electronics Abstracts: Jan. 1991 – Apr. 1998 • EI A: The Engineering Index Annual: 1987 – 1992 • EI M: The Engineering Index Monthly: Jan. 1993 – Apr. 1998 (except May 1997) • Esp@cenet patents – Apr. 2002 • IEEE: IEEE and IEE Journals – Fall 2002 • N: Scientific and Technical Aerospace Reports: Jan. 1993 - Dec. 1995 (except Oct. 1995) • NASA NASA ADS www bibliography database: – Dec. 2002 • P: Index to Scientific & Technical Proceedings: Jan. 1986 – Dec 1999 (except Nov. 1994) • PA: Physics Abstracts: Jan. 1997 – June 1999 • PubMed: National Library of Medicine Jan. 2000 – Oct. 2000 • SPIE Web The International Society for Optical Engineering – June 2002 1 2 1.1 Genetic algorithms and neural networks Your contributions erroneous or missing? The bibliography database is updated on a regular basis and certainly contains many errors and inconsistences. The editor would be glad to hear from any reader who notices any errors, missing information, articles etc. In the future a more complete version of this bibliography will be prepared for the genetic algorithms and neural networks research community and others who are interested in this rapidly growing area of genetic algorithms. When submitting updates to the database, paper copies of already published contributions are preferred. Paper copies (or ftp ones) are needed mainly for indexing. We are also doing reviews of different aspects and applications of GAs where we need as complete as possible collection of GA papers. Please, do not forget to include complete bibliographical information: copy also proceedings volume title pages, journal table of contents pages, etc. Observe that there exists several versions of each subbibliography, therefore the reference numbers are not unique and should not be used alone in communication, use the key appearing as the last item of the reference entry instead. Complete bibliographical information is really helpful for those who want to find your contribution in their libraries. If your paper was worth writing and publishing it is certainly worth to be referenced right in a bibliographical database read daily by GA researchers, both newcomers and established ones. For further instructions and information see ftp.uwasa.fi/cs/GAbib/README. 1.1.1 How to cite this report? You can use the BiBTEX file GASUB.bib, which is available in our ftp site ftp.uwasa.fi in directory cs/report94-1 and contains records for GA subbibliographies for citing with LATEX/BibTEX. 1.2 How to get this report via Internet? Versions of this bibliography are available via anonymous ftp or www from the following site: media web country Finland site lipas.uwasa.fi directory ~TAU/reports/report94-1 file gaNNbib.pdf The directory also contains some other indexed GA bibliographies shown in table A.1. In case you do not find a proper one please let us know: it may be easy to tailor a new one. 1.3 Acknowledgement The editor wants to acknowledge all who have kindly supplied references, papers and other information on genetic algorithms and neural networks literature. At least the following GA researchers have already kindly supplied their complete autobibliographies and/or proofread references to their papers: Dan Adler, Patrick Argos, Jarmo T. Alander, James E. Baker, Wolfgang Banzhaf, Helio J. C. Barbosa, Hans-Georg Beyer, Christian Bierwirth, Peter Bober Joachim Born, Ralf Bruns, I. L. Bukatova, Thomas Bäck, Chhandra Chakraborti, Nirupam Chakraborti, David E. Clark, Carlos A. Coello Coello, Yuval Davidor, Dipankar Dasgupta, Marco Dorigo, J. Wayland Eheart, Bogdan Filipič, Terence C. Fogarty, David B. Fogel, Toshio Fukuda, Hugo de Garis, Robert C. Glen, David E. Goldberg, Martina GorgesSchleuter, Hitoshi Hemmi, Vasant Honavar, Jeffrey Horn, Aristides T. Hatjimihail, Heikki Hyötyniemi Mark J. Jakiela, Richard S. Judson, Bryant A. Julstrom, Charles L. Karr, Akihiko Konagaya, Aaron Konstam, John R. Koza, Kristinn Kristinsson, Malay K. Kundu, D. P. Kwok, Jouni Lampinen, Jorma Laurikkala, Gregory Levitin, Carlos B. Lucasius, Timo Mantere, Michael de la Maza, John R. McDonnell, J. J. Merelo, Laurence D. Merkle, Zbigniew Michalewics, Melanie Mitchell, David J. Nettleton, Volker Nissen, Ari Nissinen, Tatsuya Niwa, Tomasz Ostrowski, Kihong Park, Jakub Podgórski, Timo Poranen, Nicholas J. Radcliffe, Colin R. Reeves, Gordon Roberts, David Rogers, David Romero, Sam Sandqvist, Ivan Santibáñez-Koref, Marc Schoenauer, Markus Schwehm, Hans-Paul Schwefel, Michael T. Semertzidis, Davil L. Shealy, Moshe Sipper, William M. Spears, Donald S. Szarkowicz, El-Ghazali Talbi, Masahiro Acknowledgement 3 Tanaka, Leigh Tesfatsion, Peter M. Todd, Marco Tomassini, Andrew L. Tuson, Kanji Ueda, Jari Vaario, Gilles Venturini, Hans-Michael Voigt, Roger L. Wainwright, D. Eric Walters, James F. Whidborne, Stefan Wiegand, Steward W. Wilson, Xin Yao, Xiaodong Yin, and Ljudmila A. Zinchenko. The editor also wants to acknowledge Elizabeth Heap-Talvela for her kind proofreading of the manuscript of this bibliography and Tea Ollanketo and Sakari Kauvosaari for updating the database. Prof. Timo Salmi and the Computer Centre of University of Vaasa is acknowledged for providing and managing the online ftp site ftp.uwasa.fi, where these indexed bibliographies are located. Chapter 2 Introduction “Many scientist, possibly most scientist, just do science without thinking too much about it. They run experiments, make observations, show how certain data conflict with more general views, set out theories, and so on. Periodically, however, some of us—scientists included—step back and look at what is going on in science.” David L., Hull, [7] The table 2.1 gives the queries that have been used to extract this bibliography. The query system as well as the indexing tools used to compile this report from the BiBTEX-database [8] have been implemented by the author mainly as sets of simple awk and gawk programs [9, 10]. string neural net neural net Neural Neuro field ANNOTE TITLE JOURNAL JOURNAL class Neural Neural Neural Neural networks networks journal journal Table 2.1: Queries used to extract this subbibliography from the source database. Hint 4 Chapter 3 Statistical summaries This chapter gives some general statistical summaries of genetic algorithms and neural networks literature. More detailed indexes can be found in the next chapter. References to each class (c.f table 2.1) are listed below: • Neural journal 56 references ([11]-[66]) • Neural networks 1820 references ([67]-[1886]) Observe that each reference is included (by the computer) only to one of the above classes (see the queries for classification in table 2.1; the textual order in the query gives priority for classes). 3.1 number of items 14 9 40 618 1064 6 63 30 15 18 1877 Table 3.1: Distribution of publication type. Publication type This bibliography contains published contributions including reports and patents. All unpublished manuscripts have been omitted unless accepted for publication. In addition theses, PhD, MSc etc., are also included whether or not published somewhere. Table 3.1 gives the distribution of publication type of the whole bibliography. Observe that the number of journal articles may also include articles published or to be published in unknown forums. 3.2 type book section of a book part of a collection journal article proceedings article proceedings report PhD thesis MSc thesis others total year 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 total Annual distribution Table 3.2 gives the number of genetic algorithms and neural networks papers published annually. The annual distribution is also shown in fig. 3.1. The average annual growth of GA papers has been approximately 40 % during late 70’s - early 90’s. items 6 21 60 156 198 246 131 84 28 13 16 10 1 year 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 items 9 63 115 151 201 165 101 65 18 9 6 4 1877 Table 3.2: Annual distribution of contributions. 5 6 3.3 Genetic algorithms and neural networks Classification 3.4 Authors Table 3.4 gives the most productive authors. Every bibliography item has been given at least one describing keyword or classification by the editor of this bibliography. Keywords occurring most are shown in table 3.3. Total neural networks engineering hybrid control image processing pattern recognition machine learning medicine robotics comparison signal processing genetic programming controllers economics parallel GA time series fuzzy systems neural network implementation classification evolution strategies review manufacturing physics diagnosis chemistry patent remote sensing optimization classifiers scheduling medical imaging tutorial artificial life analysing GA rule based systems games coevolution others 1875 1549 152 147 99 60 57 56 47 46 39 36 33 32 30 29 27 27 26 23 23 19 18 17 16 16 16 14 13 13 13 12 12 11 11 11 10 10 10 3701 Table 3.3: The most popular subjects. total number of authors Fogel, David B. Garis, Hugo de Cliff, David T. Harvey, Inman Husbands, Philip Whitley, Darrell Fukuda, Toshio Yao, Xin Sendhoff, Bernhard McDonnell, John R. Omatu, Sigeru Samad, Tariq Shibata, Takanori Zhang, Byoung-Tak 3 authors 6 authors 7 authors 16 authors 24 authors 50 authors 115 authors 391 authors 2518 authors 3144 25 25 22 21 20 19 18 15 11 10 10 10 10 10 9 8 7 6 5 4 3 2 1 Table 3.4: The most productive genetic algorithms and neural networks authors. Authors 7 6Genetic algorithms and neural networks ccc c ccc c cc 1000 c c number of papers c c (log scale) cccccc c ssssss s c s ss 100 cc c s cc ss c s c s s s c cc s s c c cc cccc 10 s s s cc s c c c c s c cc c c c 1c cc s 1960 2012/06/28 1970 1980 1990 2000 2010 year Figure 3.1: The number of papers applying genetic algorithms and neural networks (•, N = 1883 ) and total GA papers (◦, N = 21690 ). Observe that the last few years are most incomplete in the database. 8 3.5 Genetic algorithms and neural networks Geographical distribution Table 3.5 gives the geographical distribution of authors, when the country of the author was known. Over 80% of the references of the GA source database are classified by country. 2012/06/28 country Total United States Japan United Kingdom Germany China Italy South Korea Finland Australia Taiwan Spain France India Belgium Canada Brazil Poland The Netherlands The Czech Republic Singapore special n % 1733 100.00 407 23.49 216 12.46 177 10.21 138 7.96 98 5.65 55 3.17 52 3.00 46 2.65 42 2.42 41 2.37 40 2.31 37 2.14 33 1.90 27 1.56 27 1.56 26 1.50 24 1.38 21 1.21 16 0.92 15 0.87 comparison δ[%] ∆[%] −3.64 +0.45 +0.11 +1.19 +0.45 +0.31 +0.76 −1.19 −0.02 +0.12 +0.33 −0.45 +0.22 +0.73 −0.05 +0.50 +0.50 +0.21 +0.19 +0.06 −13 +4 +1 +18 +9 +11 +34 −31 −1 +5 +17 −17 +13 +88 −3 +50 +57 +21 +26 +7 all N 20498 5562 2461 2070 1387 1066 586 460 787 501 461 405 530 345 171 330 205 180 205 150 167 % 100.00 27.13 12.01 10.10 6.77 5.20 2.86 2.24 3.84 2.44 2.25 1.98 2.59 1.68 0.83 1.61 1.00 0.88 1.00 0.73 0.81 Table 3.5: The geographical distribution of the authors working on genetic algorithms and neural networks (n) compared (δ and ∆) to all authors in the field of GAs (N ). In the comparison column: δ% = nNT otal %special−%all and ∆ = (1 − N nT otal ) × 100%. ∆ is the relative (%) deviation from the expected number of special papers. Observe that joint papers may have authors from several countries and that not all authors have been attributed to a country. 3.6 Conclusions and future The editor believes that this bibliography contains references to most genetic algorithms and neural networks contributions upto and including the year 1998 and the editor hopes that this bibliography could give some help to those who are working or planning to work in this rapidly growing area of genetic algorithms. Chapter 4 Indexes 4.1 Books ?, [935] Acta Electronica Sinica (China), The following list contains all items classified as books. Adaptive Behavior, [1215] [88, 746, 945] Adv. Robot. (Netherlands), [1799] Advanced Technology for Developers, [134, 135, 293, 294, 401] Algorithmes Génétiques et Réseaux de Neurones, [862] Advances in Applied Mathematics, [76] C++ Power Paradigms, [1025] AI Communications, [698] Evolution of Structures - Optimization of artificial neural structures for information processing , [1844] AI Expert, [78, 120, 880] AIAA Journal, [460, 656] Evolutionary Learning Algorithms for Neural Adaptive Control, [1573] AIChE J., [1739] Anal. Chem., [547] Fundamentals of Artificial Neural Networks, Analytica Chimica Acta, [1022] Fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms: Industrial Applications, [1642] [107, 807, 1501] Annals of Biomedical Engineering, [636] Appl. Intell. Int. J.Artif. Intell. Neural Netw. Complex Probl-Solving Technol (Netherlands), [37, 38] Intelligent System Applications in power Engineering, Evolutionary Programming and Neural Networks, Appl. Intell., Int. Artif. Intell. Neural Netw. Complex Probl.-Solving Technol. (Netherlands), [1336] [1644] Modellierung von unvollständig beschriebenen Systemen, Appl. Intell., Int. J. Artif. Intell. Neural Netw. Complex Probl.-Solving Technol (Netherlands), [41] [568] Neural Network Training Using Genetic Algorithms, [1349] Appl. Intell., Int. J. Artif. Intell. Neural Netw. Complex Probl.-Solving Technol. (Evolutionary), [1723] Neural Networks and Genetic Algorithms – Business Applications and Case Studies, [292] Appl. Nonlinear System Identification: from Classical Approaches to Neural Networks and Fuzzy Models, [615] Intell., Int. J. Artif. Intell. Complex Probl.-Solving Technol. Neural Netw. (Netherlands), [44, 1671, 48, 1720] Parallel Processing in Neural Systems and Computers, [170] Appl. Intell., Int. J. Atif. Intell. Neural Netw. Complex Probl.-Solving Technol. (Netherlands), [51] Vještačka inteligencija & fuzzy-neuro-genetika, Appl. Math. Modelling, Wavelets in Soft Computing, [737] [603] Applied Intelligence, [1357] [496, 1675] Applied Mathematics and Computation, total 14 books Applied Soft Computing, 4.2 Journal articles The following list contains the references to every journal article included in this bibliography. The list is arranged in alphabetical order by the name of the journal. [779, 780] Applied Spectroscopy, [768, 793] Aquatic Ecology, [591] Artif. Intell. Eng. (UK), [1432] Artif. Life Robot. (Japan), Artificial Intelligence, [1730, 1790] [1418] [491] Artificial Intelligence in Engineering (UK), Artificial Intelligence in Medicine, Artificial Intelligence Review, 9 [582] [1364] [1290, 1836] 10 Genetic algorithms and neural networks Artificial Life, Electr. Eng. Jpn, [879, 1135, 1140, 1519] Atmospheric Environment, Aust. J. Intell. Inf. Process. Syst. (Australia), Autom. Electr. Power Syst. (China), Autom. tech. Prax. (Germany), [1124] Electr. Eng. Jpn (USA), [761] [1691] Electr. Power Syst. Res. Eng. Jpn, [1633] Electric Power Systems Research, [1374] Electronics Letters, [1690] [361, 392, 707, 887, 1516] [1570] Endocytobiosis and Cell Research, Bioinformatics, [1697] Energy and Buildings, Biological Cybernetics, [182, 343, 590] Eng. Technol. (Japan), [288] Automatica, Biomedical Soft Computing and Human Sciences, Biophysical Journal, Eur. J. Pharm. Biopharm., [727] [556] [1696, 1828, 1853] [1179] Bull. Pol. Acad. Sci. Tech. Sci. (Poland), [1448] Expert Systems, [918] [529] [1297] [741] Expert Systems with Applications, [1431] Far East Journal of Mathematical Sciences, Finite Elements in Analysis and Design, Fluid / Particle Separation Journal, Cailiao Yanjiu Xuebao, [1669] Frontiers in Neuroscience, [1148, 1881] Chemometrics and Intelligent Laboratory Systems, [309, Fuel, Chinese Journal of Advanced Software Research, [1286] [290, 352, 354, 362, 384, 428, 580, 881] Comput. Electron. Agric. (Netherlands), [1480, 1556] [950, 1090, 1188, 1820] Genetic Programming and evolvable Machines, [661] Genetic Programming and Evolvable Machines, [787] Geophysical Journal International, Computer Applications in the Biosciences (CABIOS), [931, 1054] Huagong Xuebao (Chin. Ed.), IEE Proc. Commun. (UK), [1051] [1819] [1152] Group Dicision and Negotiation, [1254] [957] [60] Giornale Italiano di Psicologia, [1787] [1464] [1795] [1643] IEE Proc., Control Theory Appl. (UK), Computer Methods and Programs in Biomedicine, [641] Computer Methods in Applied Mechanics and Engineering, [1664] [431] [553] [642] Fuzzy Sets and Systems, 654, 976, 1391] Computer Design, Evolutionary Computation, Expert Syst. Appl. (UK), Bulletin of the Polish Academy of Sciences - Chemistry, Computer, [621, 742, 1686, 1815] Bull. Sci. Assoc. Ing. Electr. Inst. Electrotech. Montefiore, [110] Comput. Intell. (USA), [1802] European Journal of Operational Research, Bull. Fac. Eng. Univ. Ryukyus (Japan), Complex Systems, [502, [1805] Eur. Trans. Electr. Power (Germany), Bull. Fac. Eng. Univ. Tokushima (Japan), Cancer Letters, [1872] 747, 1252, 1367, 1515] [776] BT Technology Journal, [1084] Engineering Applications of Artificial Intelligence, [946, 999] Biosystems Engineering, BMC Bioinformatics, [530] [1105, 1253] [874] [1771] IEEE Aerospace and Electronic Systems Magazine, IEEE Communications Magazine, [1005] [295] Computer Physics Communications, [611] IEEE Computer Society Technical Committee on Microprogramming and Microarchitecture, [398] Computers & Chemical Engineering, [749] IEEE Control Systems, [1010] [130, 1088, 1244] IEEE Control Systems Magazine, Computers & Industrial Engineering, Computers & Operations Research, [1315, 1334] IEEE Electronics Letters, [964] [1676] IEEE Expert, [200, 459, 1109, 1112, 1202] Computers and Electronics in Agriculture, [499, 1428, 1476] IEEE Expert (USA), [1381] Computers in Chemical Engineering, IEEE Geoscience and Remote Sensing Letters, Computers & Structures, Connection Science, [599, 1237] Control Cybern. (Poland), IEEE Potentials, Cybernetics and Systems, [1673] [1826] IEEE Trans. Neural Netw. (USA), Theory Appl. [1636, 50, 1852] [659] Decis Support Syst (Netherlands), Decis Support Syst. (Netherlands), Egypt. Comput. J. (Egypt), I, Fundam. IEEE Transactions of Electronics Packaging Manufacturing, [836] Decision Support Systems, [783] [201] IEEE Trans. Circuits Syst. (USA), [1797] [1377] Cybernetics and Systems Analysis, Decis Support Syst, [1616] [1077] [700] [962] [1189] [1672] IEEE Transactions on, [1792] IEEE Transactions on Aerospace and Electronic systems, [676] IEEE Transactions on Biomedical Engineering, [1747] Journal articles 11 IEEE Transactions on Circuits and Systems — I, Fundamental Theory and Applications, [124] IEEE Transactions on Circuits and Systems, II: Express Briefs, [786] IEEE Transactions on Computers, [1801] IEEE Transactions on Electronics Packing Manufacturing, [1829] IEEE Transactions on Evolutionary Computation, [578, 604, 640, 1407, 1549] [534, 593, 658, 673, 1108, 1317, 1368, 1658] Image and Vision Computing, [589] Information Sciences, [72, 1131] [505, 546, 576, 600, 895, 917, 955] Int. J. Adapt. Control Signal Process. (UK), [1823] Int. J. Appl. Electromagn. Mech. (Netherlands), [1679] Int. J. Artif. Intell. Neural Netw. Complex Probl.-Solving Technol. (Netherlands), [46, 49] Int. J. Intell. Syst. (USA), [1688] Int. J. Intell. Syst. Account. Financ. Manage. (UK), IEEE Transactions on Geoscience and Remote Sensing, [797, 1031] [1630] Int. J. Mod. Phys. C, Phys. Comput. (Singapore), IEEE Transactions on Industrial Applications, [1536] IEEE Transactions on Industrial Electronics, Int. J. Neural Syst., [617, 1361, 1751, 1818] [1076] [485] Int. J. Prod. Econ. (Netherlands), [1411] Int. J. Syst. Sci. (UK), [1600] IEEE Transactions on Industry Applications, IEEE IMA Journal of Mathematics Applied in Business and Industry (UK), [1884] Informática y Automática (Spain), IEEE Transactions on Electronics Packaging Manufacturing, [756] IEEE Transactions on Fuzzy Systems, IEICE Transactions on Information and Systems, [357, 759] Transactions on Information Biomedicine, [731] [1749] Integrated Computer-Aided Engineering, Technology in IEEE Transactions on Instrumentation and Measurement, [565, 1615, 1769] Intelligent Systems Engineering, [669, 687] [300] Intelligent Systems in Accounting, Finance & Management, [757] International Journal for Numerical Methods in Engineering, [678, 714] IEEE Transactions on Magentics, [523] IEEE Transactions on Magnetics, [484, 653] IEEE Transactions on Microwave Theory and Techniques, [1638] International Journal of Advanced Manufacturing Technology, [805] International Journal of Biological and Life Sciences, IEEE Transactions on Neural Networks, [112, 189, 273, 524, 544, 549, 577, 15, 16, 17, 623, 18, 694, 19, 20, 766, 22, 23, 858, 875, 24, 25, 936, 26, 27, 954, 28, 29, 30, 1064, 1117, 1231, 1236, 1281, 1282, 1287, 1292, 1405, 1440, 39, 42, 1569, 1628, 1666, 47, 1701, 1758, 1789] IEEE Transactions on Nuclear Science, [648] International Journal of Digital Earth, International Journal of Electronics, [67] [811] [1218] International Journal of Geriatric Psychiatry, International Journal of Intelligent Systems, International Journal of Neural Systems, [605] [482] [1096] IEEE Transactions on Pattern Analysis and Machine Intelligence, [1246] International Journal of Neural Systems (Singapore), [483] IEEE Transactions on Power Delivery, [1583, 1740] International Journal of Pattern Recognition and Artificial Intelligence, [674, 1255, 1502] IEEE Transactions on Power Systems, [1499] International Journal of Production Research, IEEE Transactions on Semiconductor Manufacturing, [1339, 1500] IEEE Transactions on Signal Processing, [1768] IEEE Transactions on Speech & Audio Processing, [559] International Journal on Intelligent Automation and Soft Computing, [1843] International Transactions in Operational Research, [1576] IEEE Transactions on System, Man, and Cybernetics, [1824] IEEE Transactions on Systems, Man and Cybernetics - Part B: Cybernetics, [649] IEEE Transactions on Systems, Man, and Cybernetics, [1196, 1296, 1322, 1609, 1660] Internet Electronic Journal of Molecular Design, [706] [743] Internet Research-Electronic Networking Applications and Policy, [695] ITB Journal of Science, [803] Izv. Akad. Nauk. Energ., [1093] J. Artif. Neural Netw. (USA), [1082] IEEE Transactions on Systems, Man, and Cybernetics Part C: Applications and Reviews, [618] J. Biomol. Struct. Dyn., IEEE Transactions on Systems, Man, and Cybernetics B, Cybernetics, [1704] J. Chin. Inst. Electr. Eng. (Taiwan), IEEE Transactions on Systems, Man, and Cybernetics, A, Systems Humans, [1311] J. Chin. Soc. Mec. Eng. Trans. Chin. Inst. Eng. Ser. C, IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences, [860, 903] IEICE Transactions on Fundamentals of Electronics, Communications and Computer Science”, , [1674] [1868] J. Chem. Inf. Comput. Sci., [497] [1755] J. Chin. Inst. Eng. Trans. Chin. Inst. Eng. Ser. A, [1326] [1069] J. Clin. Neurophysiol, [65] J. Comput. Chem., [1783] J. Comput. Inf. Technol. CIT (Croatia), [1745] 12 Genetic algorithms and neural networks J. Comput. Neurosci., Journal of the Indian Institute of Science, [64] J. Electr. Eng. Inf. Sci. (Taiwan), J. Forth Appl. Res., [959] [164] J. Fudan Univ., Nat. Sci. (China), Journal of Theoretical Biology, [1713] J. Grad. Sch. Fac. Eng. Univ. Tokyo A (Japan), J. Inst. Electron. Eng. Korea C (South Korea), [1877] [1785] J. Inst. Electron. Eng. Korea S (South Korea), [1603, 1619, 1640, 1757] J. Inst. Image Electron. Eng. Jpn. (Japan), [823] J. Intell. Robot. Syst. Theory Appl. (Netherlands), [1756] J. Jpn. Soc. Simul. Technol. (Japan), [1402] J. KISS(B), Softw. Appl. (South Korea), J. Korea Inf. Sci. Soc. (South Korea), J. Korea Inst. Telemat. [934, 1098] Electron. (South Korea), [66] [1325, 1400, 1420] J. Soc. Instrum. Control Eng. (Japan), J. Softw. (China), Lancet, [1173] Machine Learning, [475] Mater Sci Eng C Biomimetic Mater Sens Systmatische Operationsforschung und Statistik, [1878] Mech. Res. Commun. (UK), [1708] Mechanical Systems and Signal Processing, [1481] [680] [507] Mem. Tokohu Inst. Technol. I, Sci. Eng. (Japan), Methods of Information in Medicine, Microelectronics Journal, Mini-Micro Syst. (China), [1106] [1304, 1710] [1116] Mosc. Univ. Comput. Math. Cybern. (USA), J. Tsinghua Univ., Sci. Technol. (China), Journal of Aerospace Power, [516] Journal of Applied Physics, [1205] Journal of Applied Physiology, [1759] Neural Comput. Appl. (UK), [1382] [1821] Journal of Chemical Information and Computer Sciences, [632] [754] Journal of Computer Information Systems, [622] [693] [721] [1235, 1272, 1337] Journal of Intelligent and Fuzzy Systems, Journal of Intelligent Robotic Systems, Neural Computat. Appl., Neural Computation, [1732] [1340] [1521] [12, 14] Neural Computing & Applications, [843, 40, 43] Neural Computing & Applications, [614, 702] Neural Computing and Applications, Journal of Korean Institute of Telematics and Electronics, [1880] [1677] Neural Netw. World (Czech Republic), [33, 1256, 36, 1474, Neural Network Review, [144] Neural Network World, [373, 13, 31, 1078, 32, 1144, 34] [11, 303, 462, 503, 575, 854, 863, 906, 975, 1225, 1538, 45] Neural Parallel Sci. Comput, [842, 52] Neural Parallel Sci. Comput. (USA), Journal of Management Information Systems, Journal of Materials Processing Technology, [683] [609, 788] [317] [729] [1261, 1330] Journal of Microcomputer Applications, [168, 1122] [21] Journal of Neuroscience Techniques, [62] Journal of Physics D-Applied Physics, Journal of Propulsion and Power, [791] [688] Journal of Qing Hua University, [1110] Journal of Sound and Vibration, [566] Journal of Systems Engineering, [198] Journal of Technical Physics (Poland), Neural Process., Neural Process. Lett. (Netherlands), Neurocomputing, [35, 55] [848] Neural Processing Letters, Journal of Mathematical Imaging and Vision, Journal of Medicinal Chemistry, [395] Neural Netw. World ( Czech Republic), Neural Networks, Journal of Japanese Society for Artificial Intelligence, [296] Journal of Mathematical Biology, [344] [1348, 1547] 53, 54] Journal of Intelligent & Fuzzy Systems, Journal of Neural Engineering, [1614] Network: Computation in Neural Systems, Journal of Artificial Intelligence Research, Journal of Global Optimization, [670] Network: Comput. Neural Syst., [1626] [1661] [525, 1744] Nature Review Neuroscience, Journal of Bioscience and Bioengineering, Journal of Food Microbiology, Nature, [1532] [418] [1584] Modell Simul Mater Sci Eng, [1703] Journal of Chemometrics, [532, 583, 728] Midwest Symp Circuits Syst, J. Shanghai Jiaotong Univ. (China), [310] Kybernetes, Medical Engineering & Physics, [1295, 1506, 1734] [1159, 1245] J. Neuroimaging, [1479] Journal of the Society of Instrument and Control Engineers, [1618] [1160] [724, 1369, 1791, 1855] [56, 581, 666, 667, 675, 681, 690, 691, 717, 725] NeuroComputing, [735] Neurocomputing, [59] Neurocomputing (Netherlands), [61, 1313, 1338, 1403, 1452, 63] NeuroImage, [58] Neuropsychobiology, [1358, 1596] New Generation Computing Journal, [958] Nippon Kikai Gakkai Ronbunshu C Hen, [209, 1049, 1145, 1267, 1268] [1134] Nippon Kikai Gakkai Ronbunshu, A-hen, [1649] Journal articles 13 NKK Technical Report (Japan), Shiyou Huagong, [1837] SIGBIO Newsletter, [98] Simulation, [1015] Nucl. Instrum. Methods Phys. Res. A, Accel. Spectrom. Detect. Assoc. Equip. (Netherlands), [1353] Soft Computing, [487, 804] Soil Science, [1838] Nucl. Instrum. Methods Phys. Res., Sect. B, Statistics and Computing, [1862] Nonlinear Analysis-Theory Methods & Applications, [1155, 1157, 1362] [1816] Nuclear Instruments & Methods in Physics Research A, [1517] [1885] Opt. Mem. Neural Netw. (USA), [1621] Superlattices and Microstructures, Surface and Coatings Technology, Syst. Comput. Jpn. (USA), [258, 1617] Systems Science (Poland), [1518] oxiao Huaxue Gongcheng Xuebao Games Econ. Behav., [1834] Pattern Anal. Appl. (UK), The International Journal of Advanced Manufacturing Technology, [624] Therapeutic Drug Monitoring, [1582] [1788] [400] The Journal of Chemical Physics, [470] [1185] [1670] [1248, 1651] Systems and Computers in Japan, [521, 1873] OR Spektrum (Germany), Parallel Computing, [839] Stud. Inf. Control (Romania), Nuclear instruments & Methods in Physics Research Section B-Beam Interactions with Materials and Atoms, Optical Engineering, Steel Research, [1456] Tien Tzu Hsueh Pao, [608] [1777] [1087] Pattern Recognition Letters, [679, 995, 1029, 1182, 1484, 1511] Trans. Inst. Electr. Eng. Jpn. C (Japan), Philosophical Transactions of the Royal Society of London B Biological Sciences, [1654] Trans. Soc. Instrum. Control Eng. (Japan), Phys. Rev. E, Stat. Phys. Plasmas Fluids Relat. Interdiscip. Top. (USA), [1387] Transactions of the Information Processing Society of Japan, [1288] Physica A, [594] Physica D, [866] Transactions of the Institute of Electrical Engineers of Japan B, [1094] Pictures of the Future, [800] Power Engineering Journal, [1531] Proc. IEEE (USA), [1854] Transactions of the Institute of Electrical Engineers of Japan D, [1397] Proc. World Congr., Int. Fed. Autom. Control, Proceedings of the IEEE, [1416] Proceedings of the National Science Council, Republic of China, Part A: Physical Science and Engineering, [1343] Protein Journal, [57] Quantitative Structure-Activity Relationships, [1593] [1320] [711] Radiophys. Quantum Electron. (USA), Remote Sensing of Environment, Renewable Energy, [922] [781] [809] Transactions on Korean Insttute of Electrical Engineers (South Korea), [1331] Ukr. Biokhim. Zh., [1446] Vistas in Astronomy, [822] Water Resour. Res., [1657] Water Resources Research, [1738] Water Science and Technology, Researches on Population Ecology, [1415] Revista del Centro de Investigación, Universidad La Salle, [486] [1667] Z. Angew. Math. Mech. (Germany), [1177] Z. Met.kd. (Germany), [1234] Zeitschrift der Deutschen Geologischen Gesellschaft, [1280] Robot. Auton. Syst. (Netherlands), Robotica, Transactions of the Institute of Systems, Control and Information Sciences, [937] Transactions of the Society of Instrument and Control Engineers (Japan), [1409] [806] Proteins: Structure, Function, and Genetics, Quim. Nova, 356, 885, 1102, 1247, 1266, 1417, 1513, 1711] Transactions of the Institute of System, Control, and Information Engineers (Japan), [1136, 1310, 1447] Transactions of the Korean Insttute of Electrical Engineers (South Korea), [1319] [506] Progress in Neurobiology, Transactions of the Institute of Electronics, Information, and Communication Engineers D-II, [1639] Transactions of the Institute of Electronics, Information, and Communication Engineers D-II (Japan), [355, [1752] Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, [736] Prog. Neurobiol., [1693] [733] Transactions of the Institute of Electrical Engineers of Japan C, [212, 1721] [1709] Proc. CSEE (China), Transactions of the ASAE, [1354, 1629] [1490] Zeitschrift für Angewandte Mathematik und Mechanik, [1003] Zhongguo Dianji Gongcheng Xuebao, [1217, 1301] [989] Robotics and Autonomous Systems, Scientific Computing World, [1443] total 618 articles in 372 series [1524] 14 Genetic algorithms and neural networks 4.3 Theses 4.3.2 The following two lists contain theses, first PhD theses and then Master’s etc. theses, arranged in alphabetical order by the name of the school. Master’s theses This list includes also “Diplomarbeit”, “Tech. Lic. Theses”, etc. Aarhus University, [853] Case Western Reserve University, 4.3.1 PhD theses George Mason University, [433] Ecole Normale Superieure de Lyon, [930] Helsinki University of Technology, Hong Kong Polytechnic University, [732] Leiden University, McGill University, [750] [102, 828] Lund Institute of Technology, [1831] [1028] [379] Tampere University of Technology, North Dakota State University of Agriculture and Applied Sciences, [286] Oregon Graduate Institute of Science and Technology, [412] Politechnika Warszawska, [1141] Ruhr-University of Bochum, Stanford University, [1599] [882] University of Dortmund, [316, 457] University of Erlangen and The University of Tennessee, [867] University of Florence, [84] University of Helsinki, [1444] University of Turku, [1648] University of Utrecht, [911] [306] The Ohio State University, [271] total 15 thesis in 13 schools The University of Kent at Canterbury, The University of Texas at Austin, University in Taiwan, [753] [1379] [777] Report series The following list contains references to all papers published as technical reports. The list is arranged in alphabetical order by the name of the institute. University of California, [855] University of Edinburgh, [393] University of Florida, 4.4 [1632] Academy of Sciences of the USSR, [113] University of Karlsruhe, [552] Carnegie-Mellon University, University of Maryland College Park, University of Missouri - Rolla, [845] [891, 904] Colorado State University, [291] [461, 464, 465, 466] Deutsches Elektronen-Synchrotron, [105] Ecole d’Ingénieurs en Informatique pour l’Industrie, [1470] University of Otago, [751] University of Oulu, [748] University of Reading, [85, 662] Ecole Normale Supérieure de Lyon, Ecole Normale Superiore, [217] [278] Edinburgh Parallel Computing Centre, University of Stellenbosch, [740] Helsinki University of Technology, [1859] University of Stirling, [228] Honeywell-Corporate Systems, University of Surrey, [1592] Institut für Neuroinformatik, [651] Institute of Psychology CNR, [342] University of Tennessee, [221] University of Washington, [117, 481] University of West Australia, [543] total 30 thesis in 27 schools Iowa State University, [970] LASPP-FER, [160] [394] [230, 232] National Research Counsil (C. N. R.), National University of Singapore, [407] [1104, 1228] Patents 15 Naval Command, [336] NIBS Pte Ltd., [849] Ohio State University, [389] Oregon Graduate Center, Politecnico di Milano, Method and apparatus for training a neural network using evolutionary programming, [192] Method and device for learning neural network, [410] [375] Technische Universität München, The University of Texas at Austin, [103] [222] [347, 840, 944, 1127] [829] University of Bonn, [80] University of Exeter, [1050] University of Florence, [1213] University of Illinois at Urbana-Champaign, University of Joensuu, [195] [421] University of San Diego, [92] University of Sussex, [339] [240, 241, 242, 243, 244, 245, 248, 257, 834, 850, 871] University of Tampere, [1426] University of Vaasa, [1860] University of Virginia, [111] total 61 reports in 41 institutes 4.5 Patents The following list contains the names of the patents of genetic algorithms and neural networks. The list is arranged in alphabetical order by the name of the patent. Artificial neural network, Neuro computer, [916] Parameter updating device for neural network, total 15 patents [1186] University of Strathclyde, [1579] [1271] Petroleum production optimization utilizing adaptive network and genetic algorithm techniques, [620] University of Karlsruhe, [378, 1139] University of Koblenz, Neural network, Pattern recognition apparatus and method of optimizing mask for pattern recognition according to genetic algorithm, [1681] Universidad de Málaga, [69, 70] Universität Karlsruhe, [522] Network topology designing device, network topology designing method and recording medium stored with network topology design program, [1803] [478] Technische Universität der Berlin, [821] Method for optimizing nn synapse combined load, [319] Ruhr-Universität Bochum, Sverdrup Technology, Learning system of recurrent neural network of coupling type, [1045] [812] Automatic freeway incident detection system using artificial neural networks and genetic algorithm, [528] Genetic algorithm synthesis of neural networks, [238] Genetic algorithm technique for designing neural networks, [403] Hybrid learning process for neural networks, e.g. for pattern recognition in speech processing - uses combination of stochastic and deterministic processes for optimizing system, [818] 16 Genetic algorithms and neural networks Authors 4.6 17 Authors The following list contains all genetic algorithms and neural networks authors and references to their known contributions. Abbod, M. F., [532] Akman, O., [60] Andersen, T., [1588] [1053, 1066] Abdala, Ricardo Skaf, [961] Alajmi, M. S., [785] Andersen, Tim L., Abdalla, M. I. A., [962] Alander, Jarmo T., [277, 1860] Anderson, C. W., [472, 475] Abdelatyzohdy, H. S., [514] Alba, Enrique, [745, 778] Anderson, Charles W., [951] Anderson, John, [1222] Anderson, Peter G., [1299, 382] Andina, Diego, [597] Anelli, P., [1685, 1687] Abdellatif, Benrebaa, [760, 769] Alba Torres, Enrique A., [69, 70, 71, 72, 73] Abe, K., [1839] Aldana Montes, José Francisco, Abou-Assaleh, Tony, [550] [69, 70, 71, 73] Abou-Zeid, Azza M., [1798] Alderighi, M., [1586] Abu-Alola, A. H., [963] Aldrich, Chris, [1616] Accornero, N., [68] Aleksander, Igor, [1744] Angelov, P., Acheroy, Marc, [1108] Alexander, D. M., [1115] Annunziato, Mauro, Adams, Paul P., [690] Alexandridis, Alex, [749] Adams, R. G., [1366] Alexandridis, Thomas K., Adams, R., [1842] Alfares, F., [785] Addis, Tom, [437] Algar, J. A., [497] Addison, J. F. D., [1781] Aliev, F., Adeli, H., [858] Alimi, A. M., Angeline, Peter J., [824, 954, 1150, 1151] [1663] [726, 773, 782, 792] Ansari, Nirwan, [1292] Anthony, Denis, [77] Antonelo, Eric Aislan, [767] Aoki, Takeshi, [1049] [1283] Aoki, Y., [1674] [1351] Aoyagi, Yuji, [1153, 1293] [1154, 1352] [797] Adgar, A., [994] Alkadhimi, K., [1042] Apolinário Jr., J. A., Aedula, Vikram, [734] Allaoui, C., [52] Ara, K., [1205] Aggarwal, R. K., [1539, 1571] Allen, Brian S., [1598] Arabas, J., [918] Arafuka, M., [865] Agui, Takeshi, [823, 1102, 355, 356, 357, 358, 446] Aguilar, J., [1347, 1582] Ahn, Seonha, [1506] Aho, Isto, [1426] Ahuja, Lajpat R., [1838] Ai, Chen, [1710] Aihara, K., [1797] Aikawa, T., [551] Aiken, Milam, [1464] Aiyoshi, E., [1354] Aizenberg, I., [589] Aizenberg, N., [589] Allen, E. B., [1191, 1419] Alpaydin, Güner, [673] Alpert, Bradley K., [74, 75, 76] Arai, K., [1354] Altiparmak, Fulya, [986] Arakaki, Toyohiro, [1735] [685] Arakawa, Takemasa, [1512, 1578] Araki, K., [1541, 1572] Alvarez, Alberto, Álvarez, Miguel A. Ávila, Alvarez, Sergio A., [607] Aly, Alaa H., [1738] Araki, Keijiro, [1194, 1424, 1550] Arao, Masaki, [967] Arbatli, A. D., [1155] [100] Arena, P., [115, 116] Ammar, Bouallegue, [760, 769] Arif, Chusnul, [803] Anagnostopoulos, C., [665] Arifovic, J., [594] Anagnostopoulos, I., [665] Arjona, Diego, [1294] Arkadan, A. A., [484] Amari, Sun-ichi, [564, 1335, 1337, 1472, 1637, 1651] [1082, 1090, 204, 209] [486] Amaral, Joao A. Arantes Do, Akamatsu, N., Arai, Fumihito, Anam, Sarawat, [808] [1622] Arkadan, Abdul-Rahman A., Akamatsu, Norio, [1732] Anand, Vic, [435] Akhtari, M., [62] Anandarajan, M., [683] Armano, G., [674] Akin, H. L., [1155] Andersen, Gregory M., [1752] Armstrong, Alun, [1641] 1545] [1361, 18 Genetic algorithms and neural networks Arnone, Salvatore, [13] Baluja, Shumeet, [971, 1296] Berk, Friedrich, [1217] Arruda, Lúcia V. R., [722] Bandar, Z., [1380] Berkholz, R., [1663] Banzhaf, Wolfgang, [604, 881] Berlanga, A., [1438, 1746] Barham, John, [77] Bernier, J. L., [974] Barnard, S. T., [97] Bertini, Ilaria, Arruda, Lucia Valéria Ramos de, [804] Arulambalam, A., [1292] Asakawa, H., [538] Asakura, Toshiyuki, [1153, 1293] Barone, Dante Augusto Couto, [1079] Asbury, Christopher T., [382] Barreto, J. M., [1625, 1645, 1724] Ase, H., [1862] Barreto, Jorge M., [1106] Atlan, Laurent, [278] Barton, S. A., [872, 1065] Atluri, Venkata, [1753] Bartscht, E., [1306] Atmar, J. Wirt, [22] Bast, T., [65] Attia, A. A., [643] Baum, Eric B., [14] Au, O. C., [1773] Baumgart-Schmitt, R., [1358, 1596] Austin, Alan Scott, [825, 79] Baxter, J., [86] [726, 773, 782, 792] Bertoni, A., [1158] Bes, F., [1358] Bessant, Conrad, [715] Bessière, Pierre, [99] Betta, G., [1615] Bevilacqua, V., [531] Bhandari, Dinabandhu, [950, 955, 431] Bhattacharjya, Anoop K., [23] Bi, T. S., [554] Biles, J. A., [1299] Billing, G., [1059] Billings, Steve A., [975] Bing, Zhang, [1304] Bingulac, Stanoje, [1196] Binstead, M. J., [82] Biondi, Joëlle, [1023] Austin, Scott, [78] Beatty, P. C. W., [540] Avdagic, Zikrija, [704, 737, 758] Beaumont, Mark A., [310] Bebis, G., [1403] Bebis, George, [973, 1298] Becerra, J. A., [600] Beckers, Jean-Marie, [685] Becks, K.-H., [87] Bishop, J. M., [281, 282] [538, 1684, 81] Beer, Randall D., [88, 89] Blair, Alan D., [1585] [1324, 1481] Behdinan, Kamran, [696] Blanchet, Max, [100] BelBruno, Joe, [1816] Blanco, A., [575] Blekas, K., [1686] Bloch, Jeffrey, [729] Blonda, Palma N., [1685] Blonda, P., [1687] Avila-Alvarez, M., [1765, 1846, 1858] Awad, Mohamad, [783] Aydin, I., [1805] Azevedo, F. M. De, [1724] Azevedo, Fernando M. de, Baba, N., Baba, Norio, Back, Barbro, [1106] [972, 1156, 1297] Badii, A., Belew, Richard K., [90, 91, 92, 93, 94] [82] Baerdemaeker, Josse De, [1101, 1476] Belfore, II, Lee A., [1361, 1545] Bafas, George, [749] Bell, S., [547] Baidyk, Tatyana N., [1013] Bellas, F., [600] Baidyk, Tatyana, [1826] Bellgard, Matthew I., [95] Bakopoulos, J., [1850] Bendu, Bai, [526] Bo, Z. Q., [1539, 1571] [1779] Boers, Egber J. W., [102] Boers, Egbert J. W., [977] Balakrishnan, Karthik, [970] Benediktsson, Helgi, Balakrishnan, K., [1172] Benediktsson, Jon A., Balasekar, S., [1292] Balbruno, J., Balicki, J., Bluff, K., [1157, 1362, 1779] [1885] Bogart, Christopher, [465, 469, 470] Bengio, Samy, [826] Bohari, A. R., [1591] Bengio, Yoshua, [826] Bohari, Abdul Rahman, [1300] [1067, 1357, 1544, 1595] [1360, 1469, 101] Bennett III, Forrest H., [508] Bolouri, H., [1842] Balkir, Sina, [673] Benoit, [56] Boonlong, K., [613] Ball, A. D., [1559] Bentink, M. W., [377] Booth, V., [63] Ball, N. R., [1162, 83, 85] Berg, P., [65] Borairi, M., [1650] Ballerini, Lucia, [1213, 84] Bergman, Aviv, [96, 97, 98] Borchardt, D., [591] Baluja, S., [49] Berk, F., [1321, 1714] Borges, Newton Chaves Kras, [978] Authors 19 Born, Joachim, [827, 919, Browse, Roger A., [1810] Cangelosi, A., [1369] Brumby, Steven, [729] Cangelosi, Angelo, [1152] Brusic, Vladimir, [1697] Cao, Meifen, [1799] 103, 104] Bornholdt, Stefan, [1280, 105, 11, 106] Borst, Marko V., [828, 977] Buckley, J. J., [1203, 1436] Capi, G., [720, 746] Bos, M., [107] Buckley, James J., [832] Caponetto, R., [115, 116] Bossomaier, Terry, [1027] Budilova, E. V., [922] Capozza, M., [68] [1437] Bosund, V., [791] Bukatova, Innesa L., [113] Carazo, J. M., Botelho, Pedro L., [1622] Bull, L., [1457] Card, H. C., [485, 1346, 1540] Boughton, Edward M., [1148, 1377] Buller, A., [1775] Bouji, M., [484] Buller, Andrzej, [501, 586] Boullart, L., [1252] Bumbaru, S., [1699] Bounds, David G., [108] Bunke, H., [1350] Bounsaythip, Catherine, [1717] Burden, Frank R., [1391] Bourbakis, N., [1705] Burdsall, B., [1365] Bower, J. M., [64] Burgard, W., [87] Boyce, J. F., [541] Burge, R. E., [114] Caruana, Richard A., [419] Boyd, R., [109] Burgess, J. M., [1387] Caruthers, James M., [490] Brameier, Markus, [604] [1054, 1521] Cardona, Xavier Vilasis, [486] Carfalhode, A., [1384] Carpentieri, M., [1158] Carreno, D., [1370] Carrier, Jean-Yves, [1161] Carse, Brian, Branke, Jürgen, [829, 979, [493, 1070, 1302, 1341, 1344] Burgos, Jose E., [1429] Casadio, Rita, Burlinson, S., [605] Caskey, Kevin Richard, [117] Burns, A., [605] Cassa, J. C., [1780] Burrows, A. P., [914, 1014] Castellano, M., [531] [1355, 1543] Castillo, Oscar, [617] Castillo, P. A., [1808] 1068, 1139] Brasil, L. M., [1625, 1645, 1724] Brassinne, P. de, la, [110] Burton, A. R., Braun, H., [1041] Burton, Anthony Richard, Braun, Heinrich, [830, 920, [1592] Bushnell, M. J., [282] Castro, Leandro Nunes de, Busse, Anja Maria, [536] Caudell, Thomas P., [118, 119] Bustillo, Eduardo, [1383] Caudill, Maureen, [120] Butchart, K., [1366] Cawley, S., [802] Butler, Darren, [1434] Cecconi, Federico, [368, 369] Butuk, N., [612] Cellier, François E., [121] [725] 1301, 1410] Brazhnik, Yuriy, [1185] Breneman, Curt, [544] Bressgott, W., [1306] Březina, T., [1597] Brill, Frank Z., [111, 112] Brotherton, T. W., [980] Buydens, Lutgarde M. C., Brotherton, Tom, [1827] Broughton, J. Q., [1116] Browder, Kathy, [787] Brown, A. D., Ceravolo, F., [794] Byrne, J. A., [386] Cha, Sang-Yeob, [1319, 1331] Cabello, D., [509] Chadderdon, T., [1827] Cade, N., [532] Chahine, J., [527] Cahill, B. J., [1871] Chaiyaratana, N., [613, 1754] Calabretta, R., [1160] Chakraborty, Subrata, [1819] [572, 309] [485, 1346, 1540] Brown, Donald E., [111, 112] Calôba, L. P., [1154, 1352] Chalmers, David J., [122] Brown, J. R., [1605] Caloba, L. P., [1622] Chan, C. Y., [1048] Brown, J., [279] Calvo, Rodrigo, [767] Chan, Shun Heng, [732] Brown, Joe R., [1610] Campadelli, P., [1158] Chan, W. T., [1727] Brown, K., [1348] Campanini, Renato, [1054] Chan, Z. S. H., [707] Brown, M., [1467] Campos, M. F. M., [1017] Chandler, B., [1359] Browne, A., [532] Canas, A., [373, 374] Chandrasekharaiah, H. S., [1479] 20 Genetic algorithms and neural networks Chanev, T. S., [40] Cheng, Yuh-Min, [636] Chowdhury, M. M. M., [1163] Chang, Ben, [172] Chengjian, Wei, [1289] Chowdhury, M., [1226] Chang, Eric I., [304] Chengjun, Huang, [1400] Choy, Wing Yiu, [1831] [895] Chang, Hsiao-Te, [1647] Chengquan, Hu, [1304] Christensen, John P., Chang, R., [1173] Chenoweth, Darrel L., [1598] Chu, C. H., Chang, Seung-Ho, [1319, 1331] Chentouf, R., [1303] Chu, Fulei, [702] Chepurnov, S. A., [922] Chu, K. H., [873] Chern, Zen-Bang, [1751] Chua, Leon O., [124] Cherruault, Y., [583] Chuang, C.-H., [1119] Chiaberge, Marcello, [1749] Chung, Fu-Lai, [593] Chiaberge, M., [1126] Chung, Hung-Yuan, [1368] Chiang, Chih-Kuan, [1368] Chung, T. S., [1653] Chiang, Tai-Lin, [659] Chunguang, Zhou, [1304] Chicano, J. Francisco, [745, 778] Ciesielski, Victor B., [868] Chiu, K.-S., [487] Ciesielski, Victor, [1807] Ciuca, I., [1422, 1621] Clarke, L. P., [66] Clergue, M., [1604] Cliff, Dave, [932] Chang, Yuan-Hsiang, [1748, 1833, 1840] Chao, Hongxing, [1373] Charlton, C. T., [1162] Chaves, R. O., [1154, 1352] Chavez, Margarita G., [396] Chehdi, Kacem, [783] Chellapilla, Kumar, [738] Chellappan, C., [1183] Chellappen, C., [1083] Chen, C. H., [1631] Chen, C. M., [554] Chen, Chin Hsing, [1318] Chen, H., [833] Chen, Heng, [1524] Chen, Hsiang-Yin, [1777] Chen, Hui-Min, [1138] Cho, Sung-Bao, [1734] Chen, Huimin, [1218] Choate, Timothy D., [25, 1282] Chen, Jong-Chen, [51] Chodakowski, Tomasz, [586] Chen, Li, [1214] Choi, B., Chen, Luonan, [1797] Chen, Ming, [596] Chen, Qiang, [789] Chen, S., [1042, 1852] Chmumy, J., [32] Cho, Byoung-Kwan, [768] Cho, Cheo-Hyeon, [1159] Cho, Hyeon-Joong, [55] Cho, Sung Bae, [1675] Cliff, David T., Cho, Sung-Bae, [1071, 1243, 1498, 1688, 1736, 1820] [1360, 1469, 1526] Chen, S.-H., Chen, Shu-Heng, Chen, Ta-Cheng, Chen, Ting-Yu, Choi, Changkyu, [1008] Choi, Doo Hyun, [1785] Choi, Doo-Hyun, [55] Choi, Hangbok, [648] Choi, Jin Young, [1224, 1478] Choi, Ju-Yeop, [1196] Choi, T. W., [1169] [1580] [1817] [1777] [553] Chongstitvatana, Prabhas, Chen, Y. M., Chen, Yan, Chen, Yen-Wei, [573] Cheng, T. C., [1802] Cluitmans, L. J. M., [383] Coete, Ian, [652] Cofiño, A. S., [741] Coghill, G. G., [1468, 301] Coir, D. W., [984] Coit, David W., [1334] Coleman, Tommy L., [1753] Colin, Andrew, [126] Collard, Philippe, [1604] Collins, S., [1073] Colmenares, A., [1347, 1582] Compiani, Mario, [1054] Compiani, M., [127] Concilio, Antonio, [1737] [18] Conrad, M., [1242] Chou, L. D., [1458] Conrad, Michael, Chou, Li-Der, [1072, 1643] Chou, You-Li, [636] Chow, C. R., [731] [826] Chou, Dashin, [806] Cheng, Shu-Chen, Cloutier, Jocelyn, [31] [563, 1712] Chen, Y.-W., [834, 850, 983, 1003, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257] Chopard, Bastien, [1124] [712] Cheng, J., [810] [1536] Chen, Ying Yin, [837, 923, 1074, 123] [837, 923, 1074, 123] Chow, T. T., [1872] [906, 969, 128, 129] Conway, A., [822] Conway, Daniel G., [1884] Cook, D. F., [502] Cooley, Donald H., [1214] Authors Cooley, Donald, 21 [512] Dasgupta, Dipankar, [1133, 337, Derouin, Edward E., [1610] Desai, V. S., [1884] Dessert, Patrick E., [816] Destri, G., [1168] 338, 339, 340, 341] Cooling, J. E., Coporaletti, Louis E., Corbacho, F., Cortez, P., Costas, Adrian, [835] Dash, P. K., [1867] Dash, S., [1867] Datta, Amlan, [839] Davey, N., [1366] Devaney, M. J., [498, 1602] Davidson, C. E., [654] Devogelaere, D., [500] Davis, Lawrence, [132, 133] Devogelaere, d., [1865] [836] [578] Deus Jr., Getúlio A de, [725] [1164, 1439] [757] Coutinho, Francisco Antonio Bezerra, [57] Cox, Kingsley J. A., [690] Dazhong, Wang, [1531] Dhar, Vasant, [18] Crawford, Kelly D., [620] De, Susmita, [1043, 1502] Dhawan, Atam P., [348, 375, 376] Creaser, P. A., [1760] De’Angelo, S., [1586] Dhawan, Atam, [877] [1625] Cremers, A. B., [87] Deazevedo, F. M., [1645] Dias, J. Da Silva, Crespo, J. L., [600] Deb, Kalyanmoy, [839] Dieckman, U., [1809] Cribbs III, H. Brown, [1490] Deboeck, Guido, [134, 135] Diessel, O. F., [377] Cristea, A., [1422] Deboeck, Tony, [134] Dill, Franz A., [136] Crook, J. N., Decarvalho, A. C. P., [1611] Di Pietra, B., [794] [1884] Di Stefano, G., [841] Dimarki, T., [540] Dinner, Aaron R., [1593] Distefano, G., [68] Dixit, Vivechana, [768] Dob, Thierry, [501] Dobbins, R. W., [159] Crucianu, Mihail, [1470] Decarvalho, L. A. V., [366] Cui, X., [519] deCastro, L. N., [1766] Cundari, Thomas R., [632] DeCegama, Angel, [284] Curry, B., [742] Decesare, Derek, [501, 586] Dachwald, Bernd, [655, 909] Dacorogna, Michel M., [31] Dagli, C. H., [1411] Dagli, C., [130] Dagli, Cihan H., [697, 1007] Dagli, Cihan, [734] Dai, Guiliang, [1087] Daido, Yosimasa, [1638] Dain, Robert A., [48] Dal Pino Jr., Arnaldo, [711] Dediu, Adrian Horia, [631] Deer, Barry C., [136] deFigueiredo, Rui J. P., [430] [1056] [842, 987, 1078, 160] [1076] Dekker, Laura, [1011] Dodd, Nigel, [161, 162, 311] De Felice, Matteo, [782, 792] Doi, K., [1210] Delgado, Antonio, [1167] Dokur, Zümray, [641, 705] Delgado, M., [575] Dolan, Charles P., [118] Delgado, Myriam Regattieri, da Rocha Costa, Antonio Carlos, Dobnikar, Andrej, Degener, T. F., [804] Dominic, Stephen, [951, 471, 472, 475] De Garis, Hugo, [1404] Dorado, Julian, [646, 1232] De Wulf, Robert R., [781] Dorey, Robert E., [836] Dempster, M. A. H., [16] Dorsey, R. E., [1672] Denaro, D., [1165] Dorsey, Robert E., [1815] [560, 562] Daly, Daniel T., [490] Damour, S., [424] Dengiz, Berna, [986] Dote, Y., Danaher, Sean, [1086, 1314] Denney, G., [1605] Doulamis, Anastasios D., DaPonte, John S., [1484] Denney, Guy, [1610] Doulamis, Nikilaos D., Darenfed, Salah, [820] Deo, Brahma, [839] Deodhar, D., [299] de’Ovidio, F., [1586] Der, R., [1256] Derigs, Ulrich, [1518] DeRouin, E., [1605, 279] Darwish, H. A., [1583, 1715, 1740] Das, P. K., Das, Rajarshi, [627] [951, 471, 474, 475] Dasgupta, D., [1720] [618, 687] [618] Doulamis, Nikolaos D., [687] Doya, K., [720, 746] Dozier, Gerry, [1772] Drabe, T., [1306] Dracopoulos, Dimitris C., [843, 926, 43, 1547, 1573] Draeger, Andreas, [964] 22 Genetic algorithms and neural networks Dreiseitl, S., [1307] Embrechts, M. J., [1865] Farag, Aly A., [1511] Dreiseitl, Stephan, [988] Embrecths, Mark J., [544] Farag, W. A., [1523, 1701] Dress, W. B., [163, 164] Emir, Damergi, [760, 769] Fariselli, Piero, [1054, 1521] [1080] Fehr, Gary, [535] Fekadu, Adhanom A., [265] Feldman, David S., [176] Feng, X., [1667] Ferariu, L., [1825] Ferguson, J. J., [177] Ferreira, Candida, [580] Ferreira, José Rui, [1864] Feuring, T., [1770, 1847] Ficon, K., [1595] Figueiredo, Mauricio, [767] Filelis, A., [380] Filho, E. F. M., [1384] Filippidis, Arthur, [1768] Fischer, Gary W., [1777] Fleischhauer, T., [1264] Fleming, Peter J., [36, 1700] Drif, Mahmoud, [809] Enab, Y. M., Du, P., [484] Enberg, Philippe Biela, [1665] Du, X., [806] Engel, Paulo M., [978] Duan, Ji-Cheng, [593] Engell, Sebastian, [964] Dubash, Neville, [676] English, T. M., [846, 1874] Dube, D., [1336] Ennaji, A., [1356] Duffield, Don W., [1024] Er, Meng Joo, [534] Duhamel, C., [37, 38] Erikawa, Y., [1324] Dumitrescu, D., [1170] Erives, Hector, [1175, 1414] Dumortier, F., [941] Erlhagen, Wolfram, [581] Dündar, Günhan, [673] Ershov, N. M., [1661] Dunis, C., [53] Ersoy, O. K., Durdanovic, Igor, [14] Duro, R. J., [600, 844] Duro, Richard J., [896] Duvigneau, R., [692] [887, 1157, 1362] Duvigneau, Regis, Dybowski, R., [1173] East, Ian R., [990] Eaton, M., [168] Ebecken, Nelson F., [1622] Eberhart, R. C., [159, 169] Eckardt, H., [261] Ecole, A. J. Ijspeert, [1741] Edelbrunner, H., [587] Eggen, Christian J., [1752] Eggenberger, P., [1385, 1822] Eilers, R., Elbuluk, Malik, Eshelman, Larry J., [419, 420, 473] Esparcia-Alcazar, Anna J., [1388] Esparcia Alcázar, Anna I., [1309] Floreano, Dario, [692] [878] Eiceman, G. A., [812] Esparcia-Alcazar, A. I., [1176] Dyabin, M. I., Eiben, Ágoston E., Escherman, Larry, Essam, Daryl, [661] Flores-Mendez, A., [770] Estevez, Pablo A., [847, 928, 991] Floridia, G., [1780] Estevez, P., [579] Floyd, C. E., [982] Ewert, Craig C., [716] Ewing, R. L., [514] Eyvazova, Z. E., [1052] Ezoe, H., [1415] Fabro, João A., [722] Fogel, Gary B., Fadda, A., [992, 1177] Fogel, Lawrence J., Fagg, Andrew H., [313] Fahn, Chin-Shyurng, [1751] Falcon, J. F., [175] Falkenauer, Emanuel, [718] Fan, H. Y., [735] Fan, Hui-Yuan, [721] Fan, Qingwu, [775] [1471] [547] [1358, 1596] [1284] Elias, John G., [883, 171, 172, 173] [503, 1178, 45, 178] Fogarty, Terence C., [1070, 1233, 1302, 1341, 1344, 179] Fogel, David B., [488, 738, 897, 28, 30, 1109, 1112, 1148, 1150, 1151, 1377, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193] [738] [28, 1109, 182, 186, 188, 192] Fong, P., [1195] Foo, Shou King, [993] Forst, C. V., [1081] Forsyth, Richard S., [194] Fortuna, L., [115, 116] Foy, Mark, [195] Foy, M., [196] Elmasry, M.I., [953] Fang, H. L., [1631] Franco, Aurali B., [396] El-Sharkawi, M. A., [956, 1308] Fang, Jian, [1432] Frank, P. M., [1678, 1825] Fang, Junlong, [796] Frankowski, Jacek, [763] El-Sharkawi, Mohamed A., [1752] Elsimary, Hamed, [1386] Fang, Kangling, [1508] Franzen, David, [776] Elsimary, H., [1174] Farag, A. S., [1802] Frayman, Y., [701] Authors 23 Fredriksson, Kimmo, [1392, 1444] Galić, Elvis, [1180] Gerbec, M., [1207] Freedman, M. T., [1376] Gallagher, John C., [88, 89] Gers, Felix, [1450] Freeman, Ernest M., [523] Gallagher, N. B., [976] Gers, F., [1404, 1775, 1848] Freisleben, Bernd, [197] Gallego, M. J., [1554] French, I. G., [994] Gámez, José A., [679] Geyer, Claudio Fernando R., Frenzel, James F., [198, 199, Gangshan, Wu, [1778] Ganguly, Nilanjan, [1819] Gant, V., [1173] 200, 201] Friedrich, C. M., Friedrich, Ch. M., [1393] [1394] Gao, X. Z., [562, 1794, [978] Gherrity, Michael, [90] Ghezelayagh, Hamid, [1776] Ghosh, Ashish, [1043, 1502] Ghoshal, J., [1209] Ghost, Prasenjeet, [490] Froese, T., [1690] Fu, Chi Yung, [1075] Gao, Xiao-Zhi, [560] Gibson, P. M., [386] Fu, F. F., [554] Gao, Xinbo, [1060, 1123] Giger, M. L., [1210] [42, 50] Ginesta, X., [1370] Giraud-Carrier, C., [1365] 1849] Fu, K., [1445] Gao, Yong, Fujii, S., [1862] Garcı́a-Gimeno, Rosa Mariá, Fujii, T., [1397, 1691] Garcia, E., [1199] Giusti, Giuliano, [1054] Fujii, Toru, [821] Garcia-Alegre, M. C., [558] Glackin, B., [802] Fujimoto, M., [1637] Gardner, Julian W., [265] Glass, C., [109] Fujimoto, Yoshiji, [1533] Gargano, Michael L., [292] Glorennec, Pierre Yves, [216] Fujita, S., [848] Garis, Hugo de, [693] [501, 512, 586, 675, 838, 958, 959, 985] Fukuda, Toshio, [967, 1082, 1090, 1128, 1145, 1512, 1548, 1564, 1578, 202, 203, 204, 205, 206, 207, 208, 209, 210] Fukumi, M., [564, 1179, [1335, 1637, Fulginei, Francesco Riganti, [653] [1812] [1378] Gokhale, Maya, [729] Garis, Hugo de, [1450] Gokulakrishnan, S., [1183] Garis, Hugo De, [1546] Golden, J. B., [997, 1199] Golubski, W., [1770, 1847] Golukakrishnan, S., [1083] Gomes, P., [1485] Garis, Hugo de, 1651, 1732, 211, 212] [567, 1372] Goggos, V., Garis, Hugo De, 1310, 1337, 1472] Fukumi, Minoru, Goerick, Christian, [1655, 1775, 1848, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158] Fullmer, Brad, [346] Gaudet, Charles, [1181] Gomez-Ramirez, Eduardo, [771, 801] Fülöp, András, [799] Gaur, S. K., [728] Gómez-Ramı́rez, Eduardo, [770, 780, 790] Funabiki, N., [1399] Gautam, Ramesh, [776] Funabiki, Nobuo, [1660] Gayko, Jens E., [533, 1430] Funabiki, S., [1397, 1691] Gedeon, Tamás D., [1031] Gomide, F., [1766] Funakoshi, Wataru, [1803] Geerestein, V. J., [1275] Gong, Wenying, [1708] Funes, Pablo, [1585] Gegout, C., [1371] Gonzales-Seco, Jose, [280] Furst, M., [362, 363] Gelsema, E. S., [995, 1182] Gonzalez, G. D., [644] Gen, Mitsuo, [1733] Gonzalez, J., [1808] Gencay, R., [594] González-Yunes, A., Furuhashi, Takeshi, [1401, 1416, Gómez-Ramı́rez, E., [668, 1765, 1846, 1856, 1858] 1689] Furuhashi, T., [1575, 1577] Furukawa, T., [1402] Furuya, Tatsumi, [1765, 1846, 1858] George, R., [1073] George, Suju M., [929] Georgilakis, Pavlos S., [687] Goto, Fumiyoshi, [1453] Good, Walter F., [1748, 1833, 1840] [898, 1190, 1227, 1248, 153] Fuyan, Zhang, [1778] Georgilakis, Pavlov S., [618] Goto, T., [1862] Gaborski, Roger S., [382] Georgilakis, P., [1850] Gotshall, Stanley, [787] Gabriele, [907] Georgiopoulos, M., [1403] Gottvald, Aleš, [1220] Galbiati, R., [1160] Georgiopoulos, Michael, [973, 1298] Gough, N. E., [963] 24 Genetic algorithms and neural networks Goulermas, Yannis J. P., [1097] Hall, T. J., [114] Harrison, G., [1408] Grabec, Igor, [691] Hallam, J. W., [60] Harrison, Leonard C., [1697] Grabensek, L., [160] Hallam, John, [59] Harrison, R. F., [324] Grabill, Paul, [1827] Hallinan, Jennifer, [1782] Hart, William Eugene, [855] [1665] Härtfelder, Michael, [197] Hartmann, Uwe, [457] Harvey, I., [1423] Graudenz, Dirk, [105, 11, 106] Hamad, Denis, Grauel, Adolf, [1217] Hämäläinen, Ari, [1000, 1085, 223] Grauel, A., Greenwood, Daniel, [1321, 1714] [385] Greenwood, Garrison W., [998, 1549, 1576] Hamedi, M., [784] Hamersma, H., [1275] Hammer, Jürgen, [1697] [1795] Grill, Warren M., [21] Han, Liqun, Grönroos, Marko A., [1648] Han, Seung-Soo, Grossi, G., [1158] Gruau, Frédéric C., [851, 930, 945, 1137, 1184, 217, 218, 219] [1187, 1260, 1327, 1339, 1500] Han, S.-S., [894] Hanai, Taizo, [1416, 1689, 1821] Grzenda, M., [1617] Guak, Kyuh-Wan, [1319, 1331] Guan, Ling, [521, 1311] Hancsók, Jenö, [799] Guan, Shanguchuan, [268] Hand, V. C., [1743] Guangxi, Li, [1530] Handmann, U., [587] Gueriot, D., [1219] Handroos, H., [1494] Gueriot, Didier, [1312, 1465] Hanebeck, Uwe D., [1188] Guertin, François, [37, 38] Hanggi, M., [1652] Hanna, Awad S., [1798] Guha, Aloke, [230, 231, 232, 233, 238] [558] Guinea, Domingo, [635] Guo, Zhichao, [220, 221] Gupta, Jatinder N. D., [546] Guthke, R., [1663] Gutiérrez, J. M., [741] Gutjahr, Steffen, [1695] Guttikonda, Padma, [501, 512] Guyer, Daniel, [499] [1796] Hadden, L. E., [681] Hahn, Lance W., [727] Hajda, P., Hajela, Prabhat, [224, 225, 226, 227, 228, 308] Hansen, J. V., Guinea, D., Gwyn, B. J., Hancock, Peter J. B., [1189, 1630, 1787] Hansen, James V., [1440] Hansen, Kim Kortermand, Hansen, L. K., [853] [1107] Harvey, Inman, [932, 1003, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257] Harvey, Neal, [729] Harvey, P. R., [541] Harvey, Robert L., [403] Hase, K., [1409] Hasegawa, Yasuhisa, [1145] Hasegawa, Y., [865] Hashimoto, R., [1639, 1823] Hashimoto, Ryoichi, [1514, 1565] Hashimoto, Yasushi, [1101, 1476] Hashimoto, Y., Häßler, A., [1001] Hassanein, Khaled, [1525] Hassoun, Mohamad H., Hatano, Hisaaki, [898] Hatano, Shoji, [898] Hatou, K., [733] Hatziargyriou, N., [1850] Hatziargyriou, Nikos D., [618, 687] [463, 468] Hao, Zhou, [642] Happel, B. L. M., [229] Happel, Bart L. M., [854] Hare, G., [1348] Hayasaka, Taichi, Harget, A., [1323] Hayashi, Yoichi, Harget, Alan, [1329] Haring, S., [1406, 1507] [431] Harkin, J., [802] [1667] [599, 1668] Harp, Steven Alex, [230, 231, 232, 233, 234, 235, 236, 237, 238] [1022, 1064, 1279, 258, 259] Hanson, Thomas, Harish, P., [733, 1515, 1556, 1694, 449] Haupt, R., [557] Haussler, A., [1290] Haverinen, Janne, [677, 710, 748, 1861] [766] [549, 832, 1436] He, Guangdong, [1433] He, Lin, [1794, 1849] He, Q., [1378] He, Qimhing, [1546] He, Yao-hua, [1837] Hakkarainen, Juha, [1186, 1212] Hakkarainen, T., [791] Harrald, P. G., [1407] He, Yongyong, [702] Hakl, F., [672] Harrington, Robert J., [1294] He, Z. Y., [1118] Hall, L. O., [66] Harris, A., [53] Hedge, M., [837] Authors 25 Heeyeung, Hwang, [934] Hirata, Masaya, [860] Hsu, T.-C., [688] Hefny, Hesham A., [1412] Hirota, K., [61] Hu, Cheng, [1528, 1703] Hegde, M., [923] Hirota, Y., [1862] Hu, L., [1802] [1568] Hegde, Shailesh U., [213] Hirst, Graeme, [426] Hu, Rong, Heimes, Felix, [1389] Hlaváček, M., [672] Hu, Shouren, [1291] Heine, Steffen, [856] Ho, Chia-Lu, [786] Hu, Yueming, [789] Heistermann, J., [857] Ho, S., [994] Hua, Ben, [1837] Ho, T. K., [707] Huang, C. M., [498, 1602] Hobday, S., [1885] Huang, Ching-Lien, Hobday, Steven, [1816] Huang, Ch.-L., [1253] Hochman, R., [1191, 1419] Huang, Jeng-Sheng, [1431] Höffgen, K.-U., [267] Huang, S. J., [956] Höhfeld, Markus, [1180] Huang, Sh.-J., [1253] Holifield, Gregory A., [719] Huang, Shyh-Jier, Holland, J. R. C., [283] Heistermann, Jochen, [818, 260, 261, 262, 263] Helden, S. P. van, [1275] Hemker, Andreas, [87] Hemmateenejad, Bahram, [743, 754] Hemmi, Hitoshi, [1450] Henderson, C. E., [496] Hendtlass, Tim, [1032, 1413, 46] [1038, 1343, 1499] [1038, 1308, 1326, 1343, 1499] Huang, Sunan, [1818] Huang, W. D., [1670] Huang, Weidong, [1669] Huang, Y., [602] Huang, Yih-Fang, [1185] Huang, Yueh-Min, [731] Huang, Zhuo, [1508] Huber, Reinhold, [1002, 1223] [1697] Huber, R., [1238] [401] Hudepohl, J. P., [1191, 1419] Hong, Seunghong, [1603] Hugget, A., [1739] Hervás-Martı́nez, César, [693] Hongxiang, Lan, [1713] Huihe, Shao, [1325] Heuvel, H. M., [309] Honkela, Timo, [1717] Huimin, Chen, [1215] Hibbs, R., [1055] Honlet, Jean, [501] Hulin, Martin, [270] Hidalgo, D., [349] Hoogenboom, G., [496] Hung, Chi C., [1753] Hung, Shih-Lin, [858, 271] Hunger, J., [1783] Hunter, A., [487, 1348] Husbands, Phil, [633] Heng, Chen, [1531] Holmes, Dawn J., [917] Heng, E. T. H., [1612] Holt, B. R., [976] Heng, Xie, [1374] Holter, T., [1088] Herdy, Michael, [264] Holzmann, Carlos A., [1375] Hering, E., [557] Homaifar, Abdollah, [268] Herman, Jeffrey S., [302] Hernáez, I., [349] Herries, G., [1086, 1314] Honeyman, Marco, Herrmann, W. M., [1358, 1596] Hong, Robert, Hervas, C., [497] Honavar, Vasant, Honda, Hiroyuki, [970, 1435] [1416, 1689, 1821] Hignite, M. A., [622, 695] Hoptroff, R. G., [114] Higuchi, Tatsuo, [1236, 1338] Horáček, P., [643] Horan, M. A., [605, 1626] Horan, Michael A., [1881] Higuchi, Tetsuya, [1227, 1801, 153] Hill, Terence, [1070] Hiltner, J., [589] Hiltunen, Teri, [747, 761] Horrocks, David H., [269] Himmelreich, Uwe, [730] Hortos, William S., [1527] Hines, Evor L., [77, 265] Hoshino, T., [296] Hussain, Talib S., [1810] Hingston, Philip, [1039] Hosokawa, S., [885, 442] Hutchins, R. G., [859] Hinton, Geoffrey E., [454] Houben, I., [1057] Hutt, B. D., [662] Hintz, Kenneth J., [1125, 266] Hough, M., [1775, 1848] Huttner, G., [1783] Hirasawa, K., [1204, 1629] Hruska, S. I., [177] Hwang, Chan Sik, [1785] Horng, Jorng-Tzong, [1201, 1627, 1784] Husbands, Philip, [932, 1003, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257] Hüsken, Michael, [533, 567, 574, 606] 26 Genetic algorithms and neural networks Hwang, Min Woong, [1224, 1478] Ishizuka, Yuichi, [916] Jeffery, Gregory, [535] Hwang, Shu-Yuen, [41] Islam, Md. Shohidul, [808] Jenkins, D. H., [614] Islam, M.N., [808] Jenkins, W. M., [1200, 1729] Islam, M.R., [808] Jensen, Craig A., [1752] Islam, M.S., [808] Jeon, Hong Tae, [1880] Ito, H., [1190] Jeon, Hong-Tae, [1640] Ivanissevich, M. L., [741] Jeon, Jeong-Yul, [1009] Jeong, Il-Kwon, [1008] Jerabek, V., [1092] Jesung, Ahn, [934] Jewajinda, Yutana, [798, 810] Ji, Zhou, [1869] Jia, P. F., [1110] Jian, Fung, [1400] Jianbo, Mao, [642] Hyötyniemi, Heikki, [1421, 1594, 1716, 1731, 1857, 1859] Iannone, R., [773] Iba, Hitoshi, [153] Iba, T., [1692] Ichikawa, Yoshiaki, [272, 273, 274] Ichimura, Takumi, Ichimura, T., Ida, K., Ivanova, P., [1091] Ivanovic, S. L., [1030] Iwasa, Y., [1415] Iwasa, Yoh, [1654] [1089, 1620] [630, 1192] [1733] Igel, Christian, [542, 581, 606, 619, 645, 650, 651, 708, 717] Iwata, Masaya, [1227, 1801] Igel, I., [587] Iwata, Naoya, [1689] Ignizio, James P., [1315] Iwata, Tadashi, [359] Ijspeert, Auke Jan, [590] Iyoda, E. M., [1766] Jiang, Jing Ping, [1433] Ijspeert, Auke J., [1742] Iyoda, Eduardo Masato, [669] Jiang, J., [1434] Ikonen, E., [780] Jacak, Witold, [988] Jianhua, Zhang, [1869] Ikuno, Yasumasa, [860] Jack, L. B., [680] Jiao, Li-Cheng, [1706] Ilakovac, Tin, [1193] Jackson, Bernie, [439] Jin, Hong-Zhong, [1794, 1849] Iliev, G., [539] Jackway, Paul, [1782] Jin, Hui-Dong, [515] Ilonen, Jarmo, [724] Jacob, C., [933, 947] Jinhui, Zou, [1710] Imada, A., [1541, 1572] Jacob, P. J., [1559] Jitaru, E., [1621] Jacobsson, Henrik, [513] Job, Dominic, [571] Jagielska, I., [1197, 1427] Jockusch, S. R., [329] Jain, Ankit, [488] Jockusch, Stefan, [863] Imada, Akira, [1194, 1424, 1550] Inaba, M., [1558] Inagaki, Yashio, [860] Inatsu, K., [1877] Inayoshi, H., [296] Jain, Lakhmi C., [1642] Ingimundarson, J. I., [1157, 1362] Jain, Sandeep D., [861] Jain, L. C., [1005, 1055, 1120, 1349, 1768, 1792] Inoue, H., [1558] Jain, Sandeep, [1340] Inoue, N., [538] Jakobi, Nick, [1198] James, Jason, [1007] Irudayaraj, Joseph M. K., [768] Irwanto, Ponix, [494] James-Roxby, Philip B., [1037] Isasi, Pedro, [1504] Jancke, Dirk, [581] Janczak, A., [1623] Jang, Dongsig, [1244] Jang, Younggun, [1603] Jansing, E. D., [1598] Janson, David J., [198, 199, 200] Jarmulak, J., [1428] Isasi, P., [1438, 1677, 1746] Ishibuchi, Hisao, [588, 1551, 1581] Ishigami, Hideyuki, [1082, 1090, 204, 208, 209] Ishiguro, A., [1049, 1693, 1822] Johns, A. T., [1534, 1539, 1571, 1709] Johnson, J. D., [1672] Johnson, John D., [836, 1815] Johnson, John L., [1656] Johnson, R. A., [695] Johnson, R. P., [1349] Johnson, R., [1120] Jones, A. H., [965] Jones, A., [1088] Jones, Albert, [1033] Jones, Antonia J., [843, 926, 966, 1547, 82] Jones, David D., [723] Jong, E. D. De, [1764] Jong, Kenneth A. De, [529, 576, 1020, 434] Ishii, Yoshikazu, [274] Jefferson, M. F., [605, 1626] Jongwan, Kim, [934] Ishikawa, M., [1425] Jefferson, Miles F., [1881] Joost, M., [413, 423] Authors Jordaan, Elsa M., 27 Kanevskij, M. F., [1093] Kefa, Cen, [642] Josephson, Eleanor M., [1024] Kang, L., [1378, 1546] Kehagias, A., [1666] Jou, Chong-Ping, Kanno, T., [1513] Keller, John G., [1646] [689] Kelley, Anne Myers, [608] [713] [1600, 1758] Joung, Chi-Sun, [1757] Kanungo, P., Joung, Je-Gun, [1845] Kao, Cheng-Yan, [1863, 1201, 1627] Jr, V. Pilla, Juang, Chia-Feng, Juedes, D. W., Jumppanen, Anne, [1830] Karaboga, D., [927, 1552] Karagianni, Hermione, [625] [1172] [1186] [1619, 1757] Jung, Jae-Byung, [1752] Jung, S., [1682] Jung, Sung Hoon, [1313, 1618] Junior, P. A. D., [1883] Junli, Zheng, [1759] Jutten, C., [1784] [658] Jun, Hyo-Byung, Justo, George Fabris, Kao, Cheng-Yen, [1079] [1303] Karayiannis, Nicolaos B., Kariya, N., [1405] [1877] Karlogirou, Soteris A., [809] Karpinski, N. G., [878] Karplus, Martin A., [1261, 1330] Karplus, Martin, [1593] Karppinen, Ari, [747, 761] Karr, Charles L., [957, 960] Karuana, Richard, [812] Kabrisky, Matthew, [1646] Kacprzyk, Janusz, [1875] Kadaba, Nagesh, [285, 286] Kadirkamanathan, V., [996, 1771] Kasabov, N., [539] Kadono, Takahashi, [1681] Kashem, M.A., [808] Kadono, Takashi, [908, 940] Kashiwagi, Shigeru, [1045] Kai, Fu, [1398] Kasparis, T., [1298, 1403] Kajihara, Nobuki, [1801] Katada, Yoshiaki, [703] Kajitani, Isamu, [1227, 1801] Kak, Subhash, [505] Kakazu, Yukinori, [886] Kakuyama, T., [823] Kalinli, A., [1552] Kaločay, Pavol, [686] Karunanithi, Nachimuthu, Kasabov, N. K., [474] [1441, 1542, 1633, 1659] Kateman, Gerrit, [309] Katic, Dusko, [1609] Kato, H., [1094] Kawabata, Hiroaki, [860] Kawady, T. A., [1583, 1715, 1740] Kemenade, C. M. H. van, [1471] Kemppainen, Harri, [1426] Kent, S., [43] Kenward, Michael, [1443] Keppler, J., [1634] Kerckhoffs, J. H., [1428] Kermani, Bahram Ghaffarzadeh, [1747] Kerszberg, M., [96] Keselman, Yakov, [716] Kewley, Robert H., [544] Khalid, Marzuki Bin, [1824] Khatib, Wael, [1700] Khiani, K. J., [1511] Kholodovuich, V. V., [1446] Khoo, Li-Pheng, [1474] Khorrami, Farshad, [861, 1340] Khoshgoftaar, T. M., [1191, 1419] Khu, S. T., [1727] Kiernan, L., [300] Kil, R. M., [1492] Kilinski, M., [1095] Kim, B. Y., [495] Kim, B., [1668] Kim, Byungwhan, [793] Kim, C. R., [1169] Kim, Chwee, [528] Kim, DaeEun, [1762] [1619] Kalos, Alex N., [713] Kawahito, Katsuhiko, [522] Kim, Dae-Joon, Kalous, R., [672] Kawamura, A., [1799] Kim, Daijin, [1506] Kaluarachchi, Jagath J., [1657] Kawano, Hiroshi, [762] Kim, Heung Bum, [1313, 1618] Kämäräinen, Joni-Kristian, Kawase, T., [1094] Kim, J. C., [1169] Kayafas, E., [665] Kim, Jeong-Gon, [1319, 1331] Kambhampati, C., [724] [1702] Kim, Jinwoo, [1010, 1202, Kamo, Masashi, [1654] Kaynak, Okyay, [1442] Kampfner, R. R., [128, 287] Kazarlis, Spyros A., [380, 381] Kim, Jong-Hwan, [1009, 1316] Kamstra, M., [1407] Keane, Andy J., [1263] Kim, Nam, [1882] Kanata, Y., [288] Keber, Christian, [15] Kim, R. S., [1882] Kandel, Abraham, [917, 1350] Keeler, J. D., [384] Kim, S. H., [1882] Kanev, Youli Andreev, [1632] Keesing, R., [438] Kim, S. W., [1169] 1317] 28 Genetic algorithms and neural networks Kim, Sang-Woon, [1674] Koga, Hisashi, [937] Krishnan, Rajendra, [868] Kim, Seong Hyun, [1880] Koh, Taek-Beom, [1319, 1331] Ku, K. W. C., [1454] Kim, Seong-Hyun, [1640] Kohagura, Y., [1828] Ku, Kim Wing C., [1789] [1654] Kim, Sungshin, [1328] Kohlmorgen, Udo, [829, 979] Kubo, Takuya, Kim, Tae Seon, [1829] Kohlmorgen, Uwe, [1012, 378] Kubota, Naoyuki, [765] Kim, Tag Gon, [1313] Kohno, Tadashi, [202, 203, 210] Kudaka, M., [1725] Kim, Y. H., [656] Kohonen, Teuvo, [1791] Kuijpers, Cindy M. H., [1456] Kim, Yong Ho, [1880] Koivisto, Hannu, [1843] King, R. E., [1812] Kingdon, Jason, [1011] Kinjo, H., [1447] Kinnebrock, Werner, [935] Kolarik, W. J., [1259] Kinsley, J. R., [163] Kolehmainen, Mikko, [747, 761] Kirby, K. G., [128, 129] Kollias, Stefanos D., [618, 687] Koivo, Heikki N., [1421, 1731, 1843, 1857] Kok, Joost N., [1208, 1406, 1471, 1507] Kuiper, Herman, [102] Kukkonen, Jaakko, [761] Kukreja, Basant, [839] Kulkarni, B. D., [1868] Kumagai, T., [1639, 1823] Kumagai, Totu, [1514, 1565] Kumano, H., [1513] Kumar, A., [1743] Kumar, K. D., [520] Kumar, K. K., [869] Kumar, Rajeev, [47] Kirk, J. S., [601] Komata, Youichirou, [1512, 1578] Kirkman, E., [1626] Kondo, T., [1693, 1822] Kishi, S., [865] Kong, Seong-Gon, [623, 1159] Kishimoto, M., [1205] Konjicija, Samim, [704, 758] Kumar, R., [1851] Kita, T., [1324, 1481] Konno, A., [1558] Kumar, Satish, [660] Kitaguchi, Takashi, [1271] Kontio, Juho, [750] Kuncheva, Ludmila I., [1216, 1452] Kitamichi, J., [1399] Koppen, M., [1475] Kundu, Malay K., [431] Kitamichi, Junji, [1660] Koppenseliger, B., [1678] Kung, C. H., [498, 1602] Kitamura, S., [1418] Kordon, Arthur K., [713] Kung, C. M., [498, 1602] Kunze, M., [1076] Kuo, L. E., [870] Kuo, R. J., [621] Kitano, Hiroaki, [866, 289, 290, 291] Korkin, Michael, [512, 535, 675, 1450, 1655] Kitowski, Z., [1067, 1544, 1595] Korkin, M., [1404, 1775, 1848] Kjellström, Gregor, [1790] Klasa, Stan, [815] Kleeck, Lawrence von, [292] Kleymenov, G., [1635] Klimasauskas, Casimir C., [293, 294, 295] Korning, Peter G., [1096] Kuo, Ting, [41] Korousic-Seljak, B., [835] Kupfermann, I., [299] Koskimies, Kai, [1426] Kupinski, M., [1210] Kosters, W., [1471] Kuriyama, Y., [1620] Kosugi, Y., [1247] Kurnaz, Mehmet Nadir, [705] Kuroda, Chiaki, [1211, 1453] [296] Kuşçu, İbrahim, [871] Kovacs, S., [1256] Kussul, Ernst M., [1013] Koza, John R., [297] Kussul, Ernst, [1826] Kozek, Tibor, [124] Kloppel, B., [1206] Kosugi, Yukio, [1268, 1788] Klosowski, M., [1448] Kouchi, M., Knight, Thomas P., [753] Kobatashi, Takahisa, [628] Kobayashi, Takeshi, [1416, 1689, 1821] Kobuchi, R., Kochergov, Evgeny, Krejsa, Jiřı́, [1597] Kremer, Stefan, [298] [1733] [1449] Kreutz, Martin, [536, 568, 650, 651, 717, 1505, 1750, 1800, 1855] Kusumoputro, Benyamin, [657] Kusunoputro, Benyamin, [494] Kvasnicka, V., [54] Kvasnička, Vladimı́r, [33] Kwaśnicka, Halina, [1553] Kocjancic, R., [1207] Kodjabachian, Jérôme, [1628, 1636] KrishnaKumar, K., [602] Kwasnicka, H., [1095] Koehn, Philipp, [867] Krishnamraju, P., [832] Kwiatkowski, Laurent, [441] Authors 29 Kwiesielewicz, M., [1455] Lee, Chi-Ho, [1316] Li, Jun, [775] Kwon, Jangwoo, [1603] Lee, C., [1733] Li, Ming, [561] Kwon, Min Ji, [793] Lee, Dong Wook, [1757] Li, Wenhua, [1060, 1123] Kwong, C. K., [624] Lee, Dong-Wook, [1607, 1763] Li, Yan-Da, [1138] [1218] Kwong, S., [1048] Lee, Eunsil, [1603] Li, Yanda, Kyngäs, Jari, [1186, 1212] Lee, H. C., [1411] Li, Y., [1001, 1163] Kyngäs, J., [1320] Lee, Hong-Gi, [1880] Li, Yongxin, [807] Kyyrö, J., [1186] Lee, Hyuek-Jae, [1044] Li, Yuanqian, [807] Lacevic, Bakir, [758] Lee, Jiann Der, [1318] Li, Yun, [1226, 1290] Lachiver, G., [1092] Lee, Jongsoo, [599] Li, Zhigang, [1291] Lackner, R., [714] Lee, Ju-Jang, [1008] Liang, Hualou, [1087] Lagaros, Nikos D., [1664] Lee, K.-H., [1836] Liang, Jimin, [647] [1708] Lai, L. L., [1796] Lee, Kwang Y., [1776] Liang, Yanchun, Lai, Loi Lei, [873, 1644] Lee, Michael A., [312] Liang, Zhiyong, [788] Lai, W. K., [301] Lee, R. S. T., [1814] Liangjie, Zhang, [1215] Laitinen, Teija, [1156, 1297] Lee, Sang-Kyung, [1244] Liao, Jun, [534] Lam, D. C., [1195] Lee, Sangmin, [1603] Liatsis, Panagiotis, [1097] Lam, H. K., [709] Lee, Seok-Hee, [1044] Licheng, Jiao, [526] Lambert-Torres, G., [1523, 1701] Lee, Seong-Whan, [1246] Liddy, E. D., [1767] Liepins, Gunar E., [303] Liew, A. C., [1867, 1612] Ligomenides, P., [166] Liguori, C., [1615] Likartsis, A., [1459] Lilichenko, Mark, [608] Lim, Jong Hwa, [1785] Lim, Young Hee, [1098] Liming, Wu, [1234] Lin, Cheng-Jiang, [1600] Lin, Cheng-Jian, [1755] Lin, Chia-Yang, [553] Lampinen, J., Lampinen, Jouni, [1510] [721, 724, Lee, S., [976] Lee, Y. H., [1871] Leefken, I., [587] Lehotsky, M., [32] Lei, Jia, [1433] Leigh, William, [700] Lemes, Maurı́cio Ruv, [711] Lent, Craig S., [1185] 1841] Lan, Kou-Torng, [1751] Land, Walker H., [518, 637] Land, Walker, [1389, 1555] Landau, David, [1866] Langenhove, L. Van, [1252] Langholz, Gideon, [872, 917] Langley, A. M., [1364, 1456] Larra naga, Pedro, [1554] Larsen, Ronald W., [302] Lau, W. S., [624] Lavine, Barry K., [654] Leung, F. H. F., [709] Leung, Henry, [676, 1161] Leung, K. F., [709] Leung, Kwong-Sak, [515] Leung, Shu H., [360] Lin, Jianya, [534] Leung, Shu-Chung, [903] Lin, Jin-Jye, [1368] Leung, S., [905] Lin, Z., [1872] Leung, Yee, [42] Ling, S. H., [709] Lewis, M. Anthony, [313] Lingireddy, Srinivasa, [1793] Lewis, O. M., [614] Lingling, Wang, [805] Li, Can, [807] Linkens, D. A., [532, 736] Li, Guo-Bin, [1794, 1849] Linkens, Derek A., [1460] [1075] Law, Diane, [840] Lawerenz, Martin, [537] Lay, Rodney K., [1294] Lazzerini, Beatrice, [1749] Lebedko, O. A., [53] [1065] Larrañaga, Pedro, Law, Benjamin, Leong, Swee, Lin, Chin-Teng, [649, 1600, 1758] [1353, 1517, 1542] Lecourtier, Y., [1356] Li, H. Y., [1539, 1571] Liong, S. Y., [1727] Lee, Chien-Min, [786] Li, JieGu, [1529] Lippmann, Richard P., [304] 30 Genetic algorithms and neural networks Lipsanen, H., [791] Lu, Yuchang, [584, 1333, Mäkinen, Erkki, [1426] Malczyk, Roman, [1220] 1537] Lipson, Hod, Lis, J., [525, 569] Lucas, S. B., [1626, 418] Lucas, S. M., [1016, 1257] Lucas, Sam B., [1881] Mammone, Richard J., [915] Lucasius, Carlos B., [309] Man, K. F., [1048] Ludwig, L. A., [1321] Ludwig, Lars A., [1217] Mang, H. A., [714] Luk, A., [905] Mangeas, M., [1221, 1466] Luk, Andrew, [903, 360] Mangel, M., [317] Luk, B. L., [1852] Maniadakis, M., [511] Luna, Francisco, [778] Maniezzo, Vittorio, [1129] Little, R. A., [1626] Litva, John, [1161] Liu, G. P., [1771] Liu, G., [996] Liu, Han-Leih, [649] Liu, Hsiao-Chung, [1431] Liu, J. N. K., [1814] Liu, J. Y., [1534] Liu, Junhua, [596, 1873] Liu, Qiang, [788] Liu, Ruey-Wen, Liu, Shuguang, Liu, Wenjuan, Liu, Y., Lund, Henrik Hautop, [1130, 1140] Luo, Y. L., [519] Luque, Gabriel, [778] Lursinsap, C., [1461] [1185] [789] [788] Mandischer, Martin, [1019, 314, 315, 316] [875, 890, Manli, Xiong, [1530] Mann, D., [605] Manneer, Tammy, [1050] Mansfeld, C., [1059] Mansourzadeh, S. A., [784] Macedo, H., [1662] Mao, K. Z., [524] Macfarlane, Donald, [311] Marabini, R., [1437] Machado, A. M. C., [1017] Marcelin, J. L., [678] [1164] [764] [1286] Liu, Yong, [1146, 1332, 1535, 1569, 1704, 1730, 1835] [1018, 1034, 1099] 318, 319] MacAllister, Donald J., [620] Liu, Wen, Mamlook, Rustom, Lo, Joseph Y., [518, 637] Machado, J., Marchand, Arnaud, [718] Lo, S. M., [735] Machado, Ricardo Jose, [131] Marchiori, E., [1208] Lo, Titus, [1161] Macias, J. A., [578] Marchiori, M., [1208] Loggi, Laura W., [1299] MacIntyre, J., [1781] Marcu, T., [1825] Lohmann, Reinhard, [1430, 307] MacLeod, Christopher, [582] Marenbach, P., [1467] [320, 321] Lopes, H. S., [1786, 1830] MacLeod, C., [1462] Margarita, Sergio, Lopes, João A. Peças, [1864] Macukow, B., [1617] Margavio, T., [622] Lopez, F., [509] Maeda, Y., [288] Maric̈ić, Borut, [322, 323] Loraschi, Andrea, [13] Magdalena, Luis, [1463] Marin, F. J., [1390] Lorincz, A., [1256] Maher, J., [772, 802] Lörincz, András, [452, 453] Mahfouf, M., [736] Mahotilo, K. V., [1251, 1679] Loskiewicz-Buczak, Anna, [1015] Marin, Francisco Javier, [416] Mariño, J., [349] Markin, Robert E., [460] Markov, A. B., [872, 1065] Markowska, U., [634] Marks, R. J., II, [408] Marks, II, Robert J., [1752, 1811] Loumos, V., [665] Maifeld, Timothy T., [874] Low, Kay-Soon, [795] Maillard, E. P., [1219] Low, W., [281] Maillard, Eric P., [1465] Lozano, R., [1856] Maillard, Eric, [1312] Marland, C., [311] Lu, Chun-Fen, [1817] Maimon, O., [362, 363] Marom, E., [428] Lu, Hongyi, [1291] Maity, Damodar, [779] Marques, Falvio D., [1222] Lu, P.-J., [688] Major, R. L., [502] Marshall, S. J., [324] Lu, Weizhen, [735] Mak, K. L., [559] Martı́, Leonardo, [325, 326] Lu, X. S., [1705] Mak, M. W., [1454] Martin, F. J. Marin, [1131] Lu, Y. C., [1285] Mak, Man Wai, [1789] Martin, N. M., [1642] Authors Martin, Noel M., 31 [1768] McGregor, Douglas R., [337, 338, Miikkulainen, R., [1671] Mikami, Sadayoshi, [1514, 1565] Mikami, S., [1639] 339, 340, 341] Martin, Worthy N., Martinez, T. R., Martinez, T., [111, 112] McInerney, Michael, [348] McInerney, M., [877] McKee, Dan, [637] McLean, D., [1380] McNay, D., [62] [1588] [1053, 1066] Martins, Weber, [961] Martins, W., [638] Marvin, A. C., [1871] Masters, Timothy D., [637] Masters, Timothy, [1555, 327] Mastronardi, G., [531] Mathews, C., [1526] Matsushita, S., [91, 92, 93] [1171] Martinez, Tony R., Matsui, Kazuhiro, McInerney, John, [1788] [1401, 1575, 1577] Mecklenburg, Klaus, [422] Meeden, Lisa A., [1322] Meesad, Phayung, [585] Meesad, P., [616] Mehmood, Hamid, [811] Mei, Shengsong, [1508] Mei, Xiaodan, [639] Miller, Geoffrey F., [850, 213, 214, 215] Miller, G., [932] Miller, Graham, [1473] Miller, Julian F., [571] Miller, K. R., [429] Milutinoviv́, Veljko, [577] Min, David I., [1777] Min, Zhang, [1400] Ming, X. G., [559] Mirea, L., [1825] Mishra, D. S., [728] Mishra, S., [1867] Matsuyama, Yasuo, [1287] Meier, Karlheinz, [1870] Mitchell, R. J., [281] Matthews, C., [1197, 1427] Meisel, Jerome, [1279] Mitra, Pabitra, [19, 20] [791] Melin, Patricia, [617] Mitra, Sushmita, [549, 19, 20] [1468] Mellit, Adel, [809] Mitrakis, Nikolaos E., [797] Melsheimer, S. S., [870] Mitsukura, Y., [564] Menczer, Filippo, [342, 343, 344] Miyajima, T., [61] Mendes, E. F., [1611] Miyamoto, Robert T., [1752] Mendoça, P. R. S., [1352] Miyazato, A., [1853] Mendonca, P. R. S., [1154] Miyazawa, Y., [520] Meng, Qing-chun, [1110] Miyoshi, T., [1229, 1272] Mizuguchi, N., [1711] Mattila, M., Maunder, R. B., Maxwell, G., Maxwell, Grant M., [1462] [582] May, G. S., [894, 1187, 1260] May, Gary S., [752, 756, 1327, 1339, 1500, 1829] Mayer, H. A., Mayer, Helmut A., [1238, 1774] [1002, 1223, 1503, 1722] Mayr, Christian, Mazarakis, Stefanos, [744, 759] [749] Merelo, J. J., [974, 1021, 1126, 1437, 1808, 373, 374] Mizuno, H., [1532] Meservy, R. D., [1189] Mizuno, Naoki, [1300] Meusinger, Reinhard, [730] Mizuno, N., [1591] Meyer, Claudia M., [375, 376] Mjolsness, Eric, [74, 75, 76] Meyer, George E., [723] Moechtar, M., [1802] Mohamad, Dzulkifli, [610] Mohamed, S., [1626] Moisa, Trandarif, [631] Mok, S. L., [624] Molina, J. M., [1438, 1746] Mazzanti, Ferran, [486] McAulay, Alastair D., [328] McCaskill, J. S., [329] McCauley, Daniel G., [626] Meyer zu Bexten, E., [589] McClendon, R. W., [496] Miagkikh, V. V., [1542] McCormack, Michael D., [620] Michel, Olivier, [1023] McCullagh, J., Michelena, M. J., [1554] Mondada, Francesco, [1178, 45] Michielssen, Eric, [62] Monostori, L., [1520] Middleton, L. T., [345] Montana, David J., [1100, 133] Montanari, D., [127] Monte, E., [349] [1360, 1469, Meyer, Jean-Arcady, [1628, 1636, 278] 1526, 101] McDaid, L. J., [802] McDonald, J. B., [1787] McDonnel, John R., [819] Miglino, Orazio, McDonnell, John R., [864, 876, 936, 330, 331, 332, 333, 334, 335, 336] [879, 1130, 370] Mihaila, D., [1132] Montufar-Chaveznava, Rodrigo, [635] Miikkulainen, Risto, McGinley, B., [772, 802] [504, 840, 925, 944, 1077, 1127, 346, 347] Moon, Sang-Woo, [623] 32 Genetic algorithms and neural networks Moon, Yoonkeon, [1010] Murray, D., [880] Narayanan, Ajit, [1050] Moor, Bart De, [448] Murray, M., [1805] Narayanan, M. N., [418] Moore, Jason H., [727] Murray-Smith, D. J., [1001] Narita, M., [1124] Moore, P. J., [1539] Murre, J. M. J., [229] Nasri, Ahmad, [783] Moores, Anthony J., [654] Murre, Jacob M. J., [854] Nassar, S., [1625] Moraga, C., [589, 1394] Murru, A., [674] Nastac, Iulian, [757] Murty, K. C. S., [1487] Nath, Sankar Kumar, [1819] Muruzábal, Jorge, [598] Nawa, N. E., [1775] Muselli, Marco, [354] Nawa, Norberto Eiji, [1655] Myers, Lemuel R., [1646] Nazarov, E., [547] Myung, Hyun, [1009] Ndeh-Che, F., [873] Na, Man Gyun, [648] Nebro, Antonio J., [778] Nacaskul, P., [53] Negoita, G., [1699] Nadeau, J.-P., [1739] Negoita, Mircea Gh., [1132] Nafasi, K., [879] Nelles, Oliver, [615] Nagabhushana, T. N., [1479] Nelson, R. D., [1787] Nagahara, Toshikuni, [860] Nelson, Ray D., [1440] Neruda, R., [545, 1560] Neruda, Roman, [1026, 1493] Neto, Joao Camargo, [723] Neumann, Ingo, [856] Neves, J., [1164, 1439] Ng, S. C., [360] Moran, F., [1437, 373, 374] Morgan, F., [772, 802] Morgan, P. H., [742] Moriarty, D. E., [1671] Moriarty, David E., [925, 944, 1077, 1127, 1379, 347] Morimoto, Tetsuo, Morimoto, T., [1101, 1476] [733, 1515, 1556, 1694, 449] Morrison, Clayton T., [518] Morshed, Jahangir, [1657] Moschytz, G. S., [1652] Motegi, A., [61] Nagahashi, Hiroshi, Motokawa, Wataru, [530] Mühlenbein, Heinz, [831, 921, 981, 1367, 350, 351, 352] Mulawka, Jan J., [823, 1102, 355, 356, 357, 358] Nagahashi, H., [1513] Nagai, Elaine Yassue, [804] Nagao, T., [1142] [814] Nagao, Tomoharu, [823, 1102, Mulet, Oriol, [486] Muller, C., [1221, 1466] Nagao, Z., [573] Ng, Sin-Chun, [903] Mun, Dae-Sik, [1319, 1331] Nagaraja, V., [1868] Ng, S., [905] Mun, S. K., [1376] Nagasaka, K., [1558] Ngam, H. W., [707] Muni, D. P., [689] Nagayama, I., [1725] Ngom, Alioune, [577] Munir-ul, M., [1226] Nagle, H. Troy, [1747] Ngom, A., [1589] Muniz, Raul E. Torrez, [1813] Najim, K., [780] Ni, Chih-Chi, [1580] 355, 356, 357, 358] Munro, Paul W., [353] Nakahashi, Hiroshi, [446] Ni, Y. X., [554] Murai, H., [1417] Nakajima, M., [1266] Nicholis, Thomas E., [58] Murakawa, Masahiro , [1227] Nakamura, N., [1629] Nickolay, B., [1475] Murakawa, Masahiro, [1801] Nakamura, Taro, [1804] Niemi, Tapio, [1426] Muramatsu, Takahiro, [1821] Nakao, Zensho, [563, 1712] Nii, Manabu, [1581] Murao, H., [1418] Nakashima, Tomoharu, [588, 1551] Nii, M., [588] Murata, J., [1204, 1629] Nakayama, Hirotaka, [359] Nikolopoulos, Chris, [948] Murata, Tadahiko, [1581] Nakazono, K., [1447] Nikolov, Z., [322] Murga, R. H., [1456] Nanda, P. K., [689] Nilson, J., [1059] Murnion, Shane, [1329] Nandi, A. K., [680] Nishikage, T., [1396] Murnion, S., [1323] Nara, S., [881] Nishikawa, Seishi, [1660] Murray, Alan, [59] Naraghipour, M., [837] Nishikawa, S., [1399] Murray, A., [1086, 1314] Naraghi-Pour, M., [923] Nishikawa, Y., [1310] Authors 33 Nishimura, H., [848] Ohm, Peter, [1367] O’Shea, Michael, [633] Nishino, K., [1425] Ohm, P., [981] Oshima, Michiharu, [1389] Nishio, Y., [1359] Ohtani, M., [61] Ošmera, Pavel, [1144] Ojeda, R. G., [1106] Ostrowski, Tomasz, Okabe, Y., [847, 928] Oussaidene, Mouloud, [31] Okamoto, J., [885] Ovaska, S. J., [562] Okano, Y., [1877] Ovaska, Seppo J., [560] Okaya, K., [1877] Overstreet, G. A., [1884] Okubo, Naofumi, [1638] Owechko, Y., [889] Okuma, Shigeru, [1049] Owen, F., [605] Okuno, Taku, [886] Owens, R., [1497] Olej, Vladimir, [699] Oyro, G., [1107] Olej, V., [32] Ozaki, Masao, [530] Oliker, S., [362, 363] Ozawa, Masanori, [1803] Oliveira, M. S. A., [609] Ozawa, S., [1684] Oliveira, R. T., [1780] Pachepsky, Yakov A., [1838] Niska, Harri, [747, 761] Nissen, Volker, [26] Nissinen, Ari S., [882, 1421, 1594, 1716, 1731, 1843, 1857, 1859] Niwa, Tatsuya, [153] Nobre, F. S. M., [1103] Noguchi, N., [1480] Noirhommefraiture, M., [1645] Noirhomme-Fraiture, M., Nolfi, S., Nolfi, Stefano, [1724] [1160] [1104, 1228, 368, 371] Nolle, Lars, [1641] Nomura, T., [1229, 1272] Nonaka, M., [1877] Padgett, Mary Lou, [1105] Novotny, V., [1667] Numata, M., [1839] Nygard, Kendall E., [285] Nyongesa, H. Okola, [1460] Obach, M., [591] Obradovic, Z., [1589] [1024, 1574, Oliver, I. M., [283] Ölmez, Tamer, [641, 705] Page, W. C., [876] Olmez, T., [887, 1516] Pagliarini, Luigi, [1130] Olsson, Björn, [513] Northmore, David P. M.,[883] Novak, Bojan, [1029, 1134, 1141, 365] Omatsu, S., [1310] Omatu, Sigeru, [694, 908, 940, 1267, 1417, 1509, 1563, 1681, 211, 212] Omatu, S., [1136, 1396, 1656, 1772] Pai, G. A. Vijayalakshmi, Pal, Sankar K., [1489] [19, 20, 950, 955, 1043, 1502, 431] Palade, V., [1699] Palagi, P. M., [366] Palaniappan, Ramaswamy, [694] 1683] Obradović, Zoran, [884] Ombuki, Beatrice, Obuchowicz, A., [1482] Onami, Saizo, Ochi, Mitsukazu, [1649] Ochiai, T., [1040] OConnell, R. M., [1536] Oda, K., [1324, 1481] Odetayo, Michael O., [774] [908, 940, 1681] Onami, S., [1136] O’Neill, A. W., [361] Palmes, Paulito P., [766] Palmieri, F., [50] Palmieri, Francesco, [24, 27] Pan, Huiyuan, [516] Pan, J. K., [1882] Pan, J. S., [1631] Pan, Q. Y., [1670] Pan, Qingyue, [1669] Pan, Zhengjun, [1546, 1842] Pan, Z., [1378] Pande, S., [802] Onishi, Masato, [1803] [1133] Ono, I., [517] Oe, S., [1417] Ono, N., [517] Oe, Syunichiro, [1225] Ontanu, Dan, [631] Oeda, S., [630] Oosthuizen, G. Deon, [364] Ogawa, Kohei, [1211, 1453] Ootani, M., [1378, 1546] Ogawa, Toshiyuki, [1579] Opitz, David W., [888, 1382] Panigrahi, Suranjan, [776] Oh, Jae Chan, [328] Oreland, Johan, [493] Pannicelli, A., [726] Oh, Se-Young, [55] Ormsbee, Lindell E., [1793] Pao, Y.-H., [952] Ohki, Toshihiko, [1821] Ornes, C., [1483] Pao, Yoh-Han, [1061] Ohkura, Kazuhiro, [703] Ortega, J., [974] Papadrakakis, Manolis, [1664] Ohkusu, Eiji, [1821] O’Shea, J. D., [1380] Papaikonomou, A., Pangabean, Martha Y., [657] [380, 381] 34 Genetic algorithms and neural networks Paparigas, D., [1850] Pegalajar, M. C., [575] Pizzuti, S., Parbhane, R. V., [1868] Pelikán, Martin, [33] Pizzuti, Stefano, [794] [726, 773, 782, 792] Paredis, Jan, [1135, 1230, Pemba, J.-P., [612] 367] Peña-Reyes, Carlos Andrés, Parikh, Jo Ann, [1484] Pendleton, Neil, Parisi, D., [1104, 1160, Pohlmann, A., [540] Polani, Daniel, Pendleton, N., Penfold, H. Bruce, [605, 1626] [1012, 377, [504, 1761, 387, 388] Poli, Riccardo, [1495, 1561, 1590, 1624, 1723] 378] 1165, 1369] [1032, 46] [1881] Parisi, Domenico, [1381, 342, 343, 344, 368, 369, 370, 371] Podlena, John R., [755] Park, Cheol Hoon, [1117, 305] Peng, Hui, [739] Politowicz, K., Park, Dae Hee, [1098] Peng, Pei-Yuan, [861, 1340] Pollack, Jordan B., [1482] [525, 569, 824, 954, 389] Park, Dai-Hee, [1245] Penmetcha, K. V., [1203] Park, J. W., [656] Penning, Leo de, [586] Park, Jaehong, [1478, 1762] Peralta, Richard C., [1738] Park, Joo-Young, [1245] Pereira, F., [1485] Park, K. S., [495] Pereira, Jr, Alfredo, [57] Park, Kyu Ho, [1313, 1618] Perez, C. A., [579, 644] Park, Lae-Jeong, [1117, 305] Perez, Claudio A., [1375] Park, S. B., [1676] Perez, Ruben E., [696] Park, Sangbong, [1117] Perez, U. A., [1274] Parker, Joel S., [727] Perkins, Simon, [729] Parra-Loera, Ramon, [1175] Perkovic, Zeljka, [1193] Parthiban, Latha, [67] Perneel, Christiaan, [1108] Poshyanonda, Pipatpong, Pasemann, F., [1614, 1809] Perona, Melissa T., [626] Pospı́chal, Jiřı́, [33] Pasquariello, G., [1687] Persson, Johanna, [379] Pospichal, J., [54] Pasquariello, Guido, [1685] Peterson, Carsten, [12] Postaire, Jack Gerard, [1665] Patel, Devesh, [1305] Petrashev, S. N., [1679] Potočnik, Primož, [691] Patel, Leena N., [59] Petrich, Loren, [1075] Pötter, Clemens, [1363] Patel, Mukesh J., [890] Petridis, V., Potter, Mitchell A., [529, 1020] Potter, W. D., [496] [1666, 380, 381] Paterakis, E., [1666] Patnaik, L. M., [372] Paton, A., [373, 374] Patro, S., Pattichis, C. S., Paul, R. J., [1057] Payne, Tom W., [16] Pazienza, Giovanni Egidio, Popovic, D., [1487] Popp, H., [1278] Porod, Wolfgang, [1185] Porter, B., [52] Porter, Reid, [729] Porter, S. J., [1871] Porto, V. W., [1377] Porto, Vincent W., [1109, 182, 186, 188, 390, 391] [891] [1866] Pham, D. T., [927, 989] Potvin, Jean-Yves, [37, 1336, 38] Philippides, A., [556] Powell, William A., [836] Philipsen, W. J. M., [383] Poza, M., [1456] Picaza, J. M., [1554] Poznyak, A. S., [1856, 1858] Pichler, B., [714] Pozzi, Sara, [548] Pichler, E. E., [384] Prados, D. L., [392] Pickering-Brown, S., [605] Prasad, Sheila, [1886] Pictet, Olivier V., [31] Prasanth, Ravi K., [460] Pietrosantro, A., [1615] Pratt, P., [892] Pilla, Jr V., [1786] Preciado, V. M., [558] [40] Pavella, M., [1486] Potter, Walter, [1231] [660] Popescu-Belis, Andrei, [1030] [345] Paul, Sandeep, [878] Petrovic, Z. R., [1259] Pattichis, Constantinos S., Polovynyuk, A. I., [771, 790, 801] Pazos, Alejandro, [1232] Pipe, Anthony G., [1070, 1233] Preciado, Victor M., [635] Peck, Charles C., [375, 376] Piskounov, A., [1635] Price, J. E., [1323] Pedone, Roberto, [370] Pitney, Gilbert, [385] Price, Jason E., [1329] Authors 35 Prieto, A., [974, 1021, 1126, 1437, 1808, 373, 374] Protzel, P., [1278] Puerta, José M., [679] Puglisi, G., [794] Puigjaner, Luis, [1167] Pujol, J. C. Figueira, [1624, 1723] Rashid, Kashif, [523] Robbins, Philip, [404] Rastogi, Ravi, [839] Roberts, Stephen G., [1035] Ravani, B., [1682] Robillard, C., [1336] Raveendran, Paramesran, Purushothaman, Gopathy, [694] Rocha, Armando Freitas da, [57, 131] Ray, K. S., [1209] Rocke, P., [772] Red’Ko, V. K., [878] Rockett, Peter, [47] Reed, R., [408] Rodriguez, J. E., [547] Reed, Russell D., [1752, 1811] Rodvold, David M., [663] Rogers, David, [165] [1405] Purvis, Russell, [700] Purwanto, W., [1556] Rogers, Leah Lucille, [306] Pyeatt, Larry, [1137, 1184] Rehder, J., [1059] Rogers, R. L., [62] Qi, Xiaofeng, [24, 27, 50] Reidys, C., [1081] Rogers, Steven K., [1646] Qiam, Yuntao, [1063] Reilly, K. D., [1203] Roh, Hyoung Ho, [752] Qiang, Wang, [1325] Reilly, Kevin D., [832] Rolfe, B. F., [701] Qing-ding, Wu, [805] Reimetz, Anja Maria, [1587] Roli, F., [674] Qiu, Hongyang, [788] Reimetz, Anja M., [1800] Rolls, E. T., [506] Qizhi, Zhang, [1234] Rekeczky, C., [1359] Romahi, Yazann, [16] Qu, Lingli, [807] Ren, Wei, [1818] Romaniuk, Steve G., Qu, Xing-Hua, [682] Renders, J. M., [862] Quintana, V. H., [1523, 1701] Renders, Jean-Michael, [1108] Reeves, Colin R., [1718, 397, 398, 399, 400] Rabelo, L. C., [1088] Rennolls, Keith, [404] Rabelo, Luis, [1033] Reyneri, L. M., [1126] Rabuñal, Juan R., [646] Reyneri, Leonardo M., [1749] Rachman, Leila F., [657] Reznik, Leonid, [34] Rad, A. B., [707] Ribeiro, A., [558] Radcliffe, Nicholas J., [393, 394, 395] Ribert, A., [1356] Radi, A., [1590] Rice, James P., [297] Richards, Edward, [715] [502] Richards, N., [1671] Ragusa, James M., [700] Richardson, Robert, [1496] Rai, Man Mohan, [684] Ridella, Sandro, [354] Rajasekaran, S., [1237, 1489] Rieffel, Eleanor G., [508] Rajkumar, N., [1796] Riessen, G. A., [1491] Rajroop, P., [873] Rijckaert, M., [500] Ramasamy, J. V., [1237] Rijkaert, M., [1865] RamBabu, P., [929] Ristov, Strahil, Ragg, Thomas, [552, 629, 698, 1273, 1410, 1695] Ragsdale, C. T., Ramı́rez, Eduardo Gómez, [486] [893, 938, 1036, 1111, 1239, 405, 406, 407] Romero, G., [1808] Ronald, Edmund, [899, 949, 424] Ronald, E., [1378, 1546] Rong-Ji, Wang, [805] Röning, Juha, [677, 710] Rooij, A. J. F. Van, [1349] Rosa, A., [1662] Rosen, S. R., [299] Rosewarne, Brendan S., [1391] Roska, Tamás, [124] Ross, B. J., [44] Ross, J., [384] Rossi, C., [1208] Röthlein, Brigitte, [800] Routen, Tom, [939] Rouvinen, A., [1494] Rovithakis, G., [511] [1193] Rowe, Jon, [990] Ritchie, Marylyn D., [727] Rowlands, H., [1240] Ramı́rez, Jaime A., [523] Ritter, Helge, [863] Roy, Nilay, [1866] Ranke, Horst, [964] Rivas, V., [1808] Roysam, Badrinath, [23] Ranson, Aaron L., [396] Rixen, Michel, [685] Ruan, Feng, [788] Rantamäki, Minna, [761] Rizki, Mateen M., [667, 402] Rubin, S., [35] Raptis, Spyros, [625] Robbel, Thaddeus A., [1656] Rubin, Stuart H., [409] 36 Genetic algorithms and neural networks Rudnick, William Michael, [410, 411, Sanjeevan, K., [1167] Schirru, Roberto, [31] Sankaranasayanan, V., [1083, 1183] Schizas, C. N., [345] Sano, Chiharu, [417] Schizas, Christos N., [1231] Schlageter, G., [1249] Schleiter, Ingrid M., [591] Schlenzig, J., [187, 190] 412] Rudolph, Günter, [29] Rudolph, S., [1241] Rudy, George, [1697] Ruggiero, J. R., [527] Santos, Antonino, [1232] Ruppin, E., [670] Santos, Antonio, [646] Russell, Jeffrey S., [1798] Santos, J., [600, 844, 896] Santibáñez-Koref, Ivan, Russo, Fabrizio, [827, 919, 103, 104] [510, 565, [17, 632, 1658] Rutkowska, D., [1673, 1726] Ruuskanen, Juhani, [747, 761] Ryu, D. H., [1169] Saad, D., [428] Sabisch, T., [1842] Saci, E. A., [583] Schmeck, Heinrich, [378] Sanz-Gonzalez, Jose L., [1879] Schmidt, K., [1451] Sanz-Gonzalez, Jose, [901] Schmidt, M., [1113, 1250] Sarabia, Luis A., [1501] Schmitz, G. P. J., [1616] Saraiva, João Tomé, [1864] Schneider, Armin, [968] Saratchandran, P., [993] Schneider, A., [1114] Saravanan, N., [897, 1112] Schneider, Gisbert, Sarimveis, Haralambos, [749] Sagara, Setsuo, Sagiroglu, S., Sagrario Sánchez, M., Saha, Swapan, Sahoo, Bishweswar, Sakasai, K., Sakihara, H., Sakr, A., [1177] Schoenaur, M., [992] Scholz, M., [425] [1832] Schoneburg, E., [1876] Sase, M., [1247] Schonfeld, R., [1451] Satalino, G., [1687] Schraudolph, Nicol N., [91, 92, 93] Satalino, Guiseppe, [1685] Schuchhardt, Johannes, Sato, Y., [1040, 1288] Sato, Yuji, [898, 1248] Satomi, K., [1637] [765] Sasaki, M., [1629] Sasaki, W., [1205] [1696] [1805] [1497] Schwaiger, R., [1238, 1774] Saxena, Ashutosh, [929] Scott, L. P. B., [527] Schafer, David, [812] Sebald, A. V., Schäfer, J., [1041] Schaffer, J. David, [419, 420, 473] Schemmel, Johannes, [1870] Sanchez, E., [1274] Scherer, A., [1249] Sànchez, V. David, [666] Scherf, Alan V., [813] Sanchis, A., [1438, 1746] Scherg, M., [65] Schiffman, Susan S., [1747] 415, 416] Schiffmann, Wolfram, Sang, Kim Chong, [934] [15] [273] [174] [1702] Schuster, Matthias G., Sawa, Toshiyuki, [653] Sandoz, D., [1870] [954] [610] [1131, 1390, [900] Schürmann, Felix, Saunders, Gregory M., Sanchez, Elie, Sandoval, F., Schultz, A., [622] [1562] [787] [744, 759] Satzinger, J., Samad, Tariq, Sampson, Jessica, Schüffny, René, [728] [579, 644] [230, 231, 232, 233, 234, 235, 236, 237, 238, 414] [931, 999, 1084] Satsangi, P. S., [1468] Salleh, Sheikh Hussain Sheikh, Salvini, Alessandro, Schoenaur, Marc, Sasaki, Hironobu, [779] Salama, R., Salomon, Ralf, [899] [844] [895] [543, 1039] Salinas, C., Schoenauer, M., Sarmiento, A., [1501] Salama, Rameri, Salcic, Z. A., [949, 424] [1477, 1557] [989] [610] [852, 931, 946, 999, 1084] Schoenauer, Marc, Sarkar, M., [1570] Salam, Md Sah Hj, [829, 979, 1012] Sanz-González, José L., [597] 1395, 1769] Russo, Marco, Schmeck, Hartmut, [1002, 1223, 1503] [180, 184, 185, 187, 190, 191] Sebastian, P., [1739] Sechi, G. R., [1586] Sedeño, Enrique Haro, [801] Seelen, Werner von, [1363, 1800] Segovia, Javier, [548, 1504] Segovia, J., [1677] Seijas, Juan, [901, 1879] Sekaj, I., [592] Selige, Thomas, [1086, 1314] [413, 421, 422, 423] Schirp, Gunnar, Schwaiger, Roland, [1518] Authors 37 Seliger, R., [1678] Selman, Bart, [426] Selvage, John E., [1598] Shih, Ching Ching, Selvam, M. A. P., [1277] Shim, M.-B., Sendhoff, Berhhard, [1372] Sendhoff, Bernhard, [533, 536, 574, 1363, 1430, 1505, 1599, 1750, 1800, 1844, 1855] Seng, Teo Lian, Senjyu, Tomonobu, [1824] [570, 1728, 1735] Senjyu, T., Singer, Joshua A., [595] Singh, B. K., [728] [1601] Singh, Kirti, [929] [566] Singh, Sanjiv Kumar, [1819] Shimizu, Masahiko, [1638] Sittisathanchai, Sinchai, [904, 130] Shimohara, Katsunori, [902, 1675] Siu, Sammy, [786] Shimohara, K., [1736] Siu, Wan Chi, [1789] Shimojima, Joji, [1548] Skabar, Andrew, [652] Skinner, A. J., [1116] [1090, 1564, 202, 203, 204, 205, 206, 207, 209, 210] Shimojima, Koji, [967, 1128, 1145] [555, 1696, 1828, 1853] Seo, Jae-Yong, [1640] Seongwon, Cho, [934] Ser, W., [524] Sere, Kaisa, Shibata, Takanori, [972, 1156, 1297] Sklansky, Jack, [1255, 1483] Shimura, A., [1680] Sklar, Elizabeth, [1585] Shin, Chulkyu, [1603] Smalz, R. W., [1242] Shin, Jin-Ho, [1008] Smalz, Robert, [906] Shin, S. C., [1676] Smillie, Matthew B., [1810] Shin, Seong-Hyo, [1674] Smith, A. E., [984] Shine, J. A., [1006] Smith, Alice E., [986, 1334] Serechenko, V. A., [878] Shinke, Noboru, [1649] Smith, D. J., [283] Sergeev, S. A., [1251, 1679] Shinohara, Yasunori, [1225] Smith, Jeff, [284] Serra, R., [127, 427] Shirakawa, Kazuo, [1638] Smith, L. S., [308] Setia, Ronald, [752, 756] Shirao, Yoshiaki, [860] Smith, R. E., [1490] Setiawan, Budi I., [803] Shively, J. W., [1377] Smith, Roger, [1816] Sette, S., [1252] Shonkwiler, Ronald, [429] Smith, R., [1885] Shukla, K. K., [489, 1584] Smith, Terence R., [385] Sidani, M., [484] Smith, Tom, [633] Siemon, H. P., [267] Smith, T., [556] [713] Sexton, R. S., [622, 695, 1672] Sexton, Randall S., [546, 1815] Shaheen, Samir I., [1412] Shamir, N., [428] Sierra, A., [578] Smits, Guido F., Shams, S., Sierra, Basilio, [1364, 1554] Smolander, S., [1510] [889] Shamsipur, Mojtaba, Sigurdsson, H. S., [1157, 1362] Smuda, Ellen, [869] [743] Snoad, Nigel, [1254] Silóniz, Maria Isabel de, [693] [1027] Shang, Yi, Shao, H. H., [1345] Silva, A., Sharif, A. M., [1745] Silva, J. Carlos Meira e, [638] Sobotka, M., [432] Sharman, K. C., [1001, 1176] Silva, M., [497] Sofge, Donald A., [664] Sharman, Ken C., [1309] Silva, N., [1662] Sohn, Sunghwan, [697] Sharman, Ken, [1388] Silva, Valceres V. R., [1700] Šojdr, Martin, [1046, 1258] Sharp, David H., [74, 75, 76] Sim, Kwee Bo, [1757, 1763] Soldatos, J., [665] Shavlik, Jude W., [888, 1382] Sim, Kwee-Bo, [1607, 1619] Sole, I., [1167] Sheblé, Gerald B., [874] Sim, Siang-Kok, [1474] Soliday, Stephen, [626] Shen, Lansun, [492] Simoes, Eduardo do Valle, Solidum, Alan, [313] Sheta, Alaa F., [576] Simon, Dan, [49] Soltani, S., [1765, 1846] Shi, C. Y., [1285] Simon, Donald L., [628] Soltys, James R., [1315] Shi, Chunyi, [584, 1537] Simpson, P. K., [980] Song, C. L, [1872] Shi, Y., [1147] Sin, Sam-Kit, [430] Song, Jing, [258, 259] [1485] [1079] So, Sung-Sau, [1261, 1330, 1593] 38 Genetic algorithms and neural networks Song, J., [806] Stathaki, A., Song, Limei, [682] Steele, Nigel C., [1812] [397, 398, 399, 400] Song, R. G., Song, Ren-Guo, Song, Renguo, Song, Yong-Hua, Song, Yoon-Seon, Sood, V. K., [1670] Steels, L., [1764] Steenstrup, Martha, [907] Steeter, Matthew J., [607] Steinmetz, U., [1809] Stender, Joachim, [437] [1878] [1669] [1534, 1709] [1492] [1796] Stepniewski, Slawomir W., Soper, Alan, [1263] [791] Sorrentino, A., [1737] Soule, Terence, [712, 787] Sousa, A. C. M., [609] Souza, A. R., [1780] Spasic, Z. A., [1030] Spears, William M., [433, 434, 435] Spiessens, Piet, [436] Spittle, Mark C., [269] Spofford, J. J., [266] Spronck, P., Srikanth, R., Srikumar, Rangarajan, Srinastava, A. K., Srivastava, A. K., Srivastava, S. K., Sriwardhana, C., Stacey, B., Stacey, Deborah A., Sundaram, Venky, [752] Sundararajan, N., [993] Sung, B. J., [656] Susu, Yao, [1289] Stidsen, T., [1113] Sutherling, W. W., [62] Stocker, E., [1356] Suykens, Johan, [448] Stoisits, Richard F., [620] Suzuki, J., [1515, 1556] Stojmenovic, I., [1589] Suzuki, Tatsuya, [1049] Stojmenović, Ivan, [577] Sveinsson, J. R., [1157, 1362] Stonham, T. J., [82] Swayne, D. A., [1195] Storey, a. M., [1195] Syed, Omar, [1028] Stork, David G., [438, 439, 440] Szekely, Geza, [1772] Szymanski, John, [729] Taalab, A. I., [1583, 1715, Stramaglia, S., [1687] Stratton, T. R., [1047] Tadel, M., [160] Stricker, R., [1264] Taggart, Ian J., [1031] Stringer, S. M., [506] Taha, Mahmoud A., [1798] Stromboni, Jean-Paul, [441] Takagawara, Y., [1324, 1481] Stroud, Phillip D., [39] Takagi, Hideyuki, [977] 1740] [817, 312, 444, 445] Su, Chao-Ton, [659] Su, D., [1265] Su, F. C., [507] Su, Fong-Chin, [636] Su, Mu-Chun, [1647] Subasinghe, H., [1796] Subramanian, R., [67] Sugai, Y., [1094] Suganami, Yusuke, [1788] Takefuji, Y., [1692] Sugawara, K., [1839] Takeuchi, Jun, [1268] Sugawara, M., [611] Takuma, Masanori, [1649] [489, 1584] [605] [1760] [298] Stafylopatis, A., [1686] Stagge, Peter, [542, 619, 708] Stan, I., [1170] 470] [490] [1685, 1687] [1584] Starkweather, Timothy John, Sundaram, Anantha, Sternieri, A., [489] [1612] [1373] [723] [884] Srinivasan, D., [639] Sun, Yan, [627] [1073] [372] Sun, Sheng-He, Surkan, Alvin J., [1428] Srinivas, M., [1373] Sural, S., [1471] Sprinkhuizen-Kuyper, Ida G., Sun, Chengyi, [1207] Stramaglia, Sebastiano, [1685] Sprinkhuizen-Kuyper, I. G., [1058] Stergarsek, A., [404] Sormunen, J., Summers, R., [466, Takahashi, H., [1266, 446] Takahashi, K., [1832] Takahashi, M., [517] Takano, Takeshi, [1089] Takano, T., [1192] Takeda, F., [1136, 1396, 1721] Takeda, Fumiaki, [908, 940, 1267, 1681] Stassinopoulos, G., [665] Sugimoto, Okamoto J., [442] Tam, P. K. S., [709] Staszewski, W. J., [1262] Sugimoto, Y., [885] Tamaki, Y., [555] State, L., [35] Sugiyama, K., [865] Tamane, Shotaro, [570] State, R., [35] Suh, M.-W., [566] Tambe, S. S., [1868] Stateczny, A., [1357] Suhardiyanto, Herry, [803] Tamburino, Louis A., [667, 402] Authors 39 Tan, K.-C., [524] Tiilikainen, Jouni, [791] Tsutsui, Shigeyoshi, [1533] Tan, Ying, [640] Tilley, David G., [382] Tsutsumi, K., [1684] Tanaka, Kazuo, [1204] Timlin, Dennis J., [1838] Tsutsumi, Yasuhiro, [967] Tanaka, K., [1629] Timofeyev, A. V., [1270] Tu, K., [733] [752] Tanaka, Masahiro, [937] Tintore, Joaquim, [685] Tummala, Rao R., Tanaka, Toshio, [153] Todd, Peter M., [213, 214, 215] Turčanı́k, Michal, [686] Tanaka, Toshiyuki, [1119] Todorova, L., [1216] Turega, Mike, [1035] Tang, K. S., [1048] Tohyama, Hisao, [1821] Turkoglu, M., [1805] Tang, Xiaojun, [1873] Tokura, S., [1822] Tzafestas, Spyros, [625] Tang, XiaoXiao, [1529] Tomassini, Marco, [31] Tzes, Anthony, [861, 1340] Tomera, M., [1455] Uchikawa, Yoshiki, [1416, 1689] Tomilinson, G. R., [914] Uchikawa, Y., Tomlinson, G. R., [1014, 1262] Tong, David W., [304] Tanie, Kazuo, [1564, 205, 206, 207] Tanino, Tetsuzo, [937] Tanprasert, T., [1461] Taraglio, S., [1269] Topaloglou, Charalampos A., Taylor, C., [797] [879] Topchy, A. P., [1575, 1693, 1822] [1353, 1517, Ueda, Kanji, [703] Uelschen, Michael, [537] Uezato, Katsumi, [570, 1728, 1735] Taylor, David, [77] Taylor, F. A., [62] Topping, B. H. V., [1566] Taylor, Stewart J., [1718] Torreele, Jan, [436, 451] Ugur, A., [969] Tazaki, Eiichiro, [1089] Toth, G. J., [1256] Uhrig, Robert E., [1015, 1567] Tazaki, E., [1192] Tóth, Gábor J., [452, 453] Uhrik, C., [196] Uichida, H., [1832] Ultsch, A., [267] Um, J. U., [1882] Unniraman, S., [1868] Urgant, O. V., [878] Urzelai, Joseba, [503] Usher, A., [282] Ushida, A., [1359] Usui, Shiro, [766] Uthmann, Thomas, [387, 388] Utrecht, U., [910] Utsugi, A., [1823] 1542] Uezato, K., Tekeuchi, T., [449] Tóth, Géza, [1185] Teller, Astro, [491, 447] Tougaw, P. Douglas, [1185] Teo, Ming-Yeong, [1474] Tourassi, G. D., [982] Terada, Kengo, [908, 940] Touretzky, David S., [454] Teramati, Y., [1513] Toussaint, Marc, [606] Terao, H., [1480] Trint, K., [910] Terekhin, A. T., [922] Tripathi, Nitin K., [811] Tettamanzi, Andrea, [13] Troya, José M., [70, 71, 73] Teunis, M., [1475] Tsai, Du-Yih, [1608, 1719] Tewari, Jagdish C., [768] Tsang, Chi Ping, [95] Theiler, James, [729] Tselioudis, George, [1484] Themlin, Jean-Marc, [1108] Tseng, Ching-Shiow, [1069] Theocharis, John B., [797] Tseng, Mei-Kuang, [1878] Thierens, Dirk, [448] Tseng, Shian-Shyong, [1778] Thompson, A. C., [1058] Tsinas, Lampros, [909] Thompson, G. W. P., [16] Tsompanakis, Yiannis, [1664] Tsoukalas, Lefteri H., [1459, 1567] Tsuji, Teruo, [1570] Tsujii, O., [1376] Tsurumaru, T., [61] Thompson, Wiley E., [1018, 1034, 1099, 1121, 1414] Thornton, Chris, Thuillard, Marc, Tian, Fengzhan, [603] [584] [1199] Vachtsevanos, George J., [1328] Vahidov, M. A., [1052] Vahidov, R. M., [1052] Vai, M. Michael, [1886] Valastro, G., [127] Valencia, S. Sanchez, [1131] Valenzuela, Christine L., [82] [871] Tsutsui, H., Tibbetts, C., [555, 1696, 1828, 1853] 1577] Valjakka, J., [1320] Valli, G., [1213] Vandewalle, Joos, [448] [1401, 1575, 40 Vanier, M. C., Genetic algorithms and neural networks Volná, Eva, [64] [671, 1522, Wang, Xiufeng, [1284] Wang, Y. F., [547] Wang, Yuan-Peng, [777] Wanrooij, E. van, [911] 1613] VanLandingham, Hugh F., Van Belle, Terry, [1196] Volná, Evo, [1276] Vonk, E., [1055, 1120] von Seelen, Werner, [645, 1372] Ward, Matthew O., [607] von Seelen, W., [587] Ware, Andrew, [1641] Voronenko, D. I., [1698] Ware, J. A., [614, 1422] Voronovsky, G. K., [1679] Warsi, N., [1073] Voss, Heiko, [1430] Warwick, Kevin, [300] Vriesenga, Mark, [1255] Warwick, K., [1702] Vukobratovic, Miomir, [1609] Wasson III, Eugene C., [1148, 1377] Waagen, Don E., [936] Watanabe, Y., [1711] Waagen, Donald E., [819, 864] Watson, Mark, [1025] Watta, Paul B., [1279] Watts, M. J., [1441, 1659] [751] [1519] Van Coillie, Frieke M. B., [781] van Eck Conradie, Alex, [740] Vann, P. A., [960] Vansteenkiste, G., [941] Vaseekar, E., [1796] Vassilev, Vesselin K., [571] Vdovichev, S., [1635] Veelenturf, L. P. J., [1055, 1120] Veenker, Gerd, [458] Velasco, Juan R., [1463] Velayutham, C. Shunmuga, Veloso, Manuela, Velthuizen, R. P., Waagen, Don, [660] [876, 330, 331, 333, 334, 335, 336] [491] Wada, Mitsuo, [1514, 1565] Watts, Michael John, [66] Wada, M., [1639, 1823] Wazlawick, Raul Sidnei, [1056] Wager, Tor D., [58] Webb, G. I., [701] [1254] Weber, H. T., [107] Venkatasubramanian, Venkat, [490] Ventresca, Mario, [774] Wah, Benjamin W., Ventura, Dan, [505, 1053] Wahab, Ashraf H Abdel, [1412] Weber, J., [1081] Ventura, D., Wahidabanu, R. S. D., [1277] Weeks, E. R., [1387] [1171] Walczak, B., [1207] Wehenkel, L., [1057] Walker, S. G., [1115] Wehrens, Ron, [572] Walker, Scott, [439] Wei, C. J., [1118] Wallrafen, J., Weihs, Claus, [1800] [1278] Weijer, A. P. de, [309] Weiß, Gerhard, [912, 942, 222] Weiss, K. R., [299] Weller, P. R., [1058] Weller, P., [1173] Verbeke, Lieven P. C., [781] Vergados, D., [665] Vermeersch, L., [941] Verschure, Paul F. M. J., [459] Vicente, J., [558] Vico, F. J., [415] Viharos, Z. J., [1520] Vilarino, D. L., [509] Vilasis-Cardona, Xavier, [771] Vilasis-Cardona, X., [668] Villani, Marco, [1054] Villmann, T., [557] Visonneau, Michel, [692] Visonneau, M., [692] Vitale, Joseph N., [1484] Vivarelli, Francesco, [1054, 1521] Vivo, Luciano de, [1737] Vlachavas, I., [1459] Vladimirova, T., [1355, 1543] Voelz, Lawrence D., Wamlook, Rustom, [1121] Wang, Aimin, [492] Wang, Chi-Hsu, [649] Wang, D. D., [1166] Wang, Dazhong, [1524] Wells, Richard B., [712] Wang, Fangju, [924] Wells, Richard, [787] Wang, H., [1650] Wen, Xu, [1531] Wang, J. W., [1631] Weng, Weiwin, [1185] Wang, Jun, [640] Wenhua, Xu, [1398] Wang, Ke-Jun, [1794, 1849] Wenhui, Chen, [1374] Wang, Lipo, [764] Wenxia, Chen, [1759] Wang, Pu, [775] Wermter, S., [1781] Wang, Q., [1345] Werner, H., [591] Wang, Shangjin, [516] Werner, R., [413, 423] Wang, Shuwen, [796] Wang, X. F., [873] [813] Wang, Xiao-Hui, Voigt, Hans-Michael, [827, 103, 104] 1840] Wesolkowski, Slawomir, [1525] Westland, S., [282] Westphal, H., [1280] Wezel, M. C., [1507] [1748, 1833, Authors 41 Wezel, Michiel C. van, [972, 1406, 1471] Wrede, Paul, [852, 931, Whitaker, Kevin W., [460] Wu, Annie S., [719] White, Bill C., [727] Wu, C. Y., [1376] White, C. R., [1024] Wu, Chen-Phon, [1069] White, David W., [845] Wu, Chia-Ju, [1756] White, D., [166] Wu, J. L. C., [1458] Whitehead, B. A., [1281] Wu, Jean-Lien C., [1072] Whitehead, Bruce A., [25, 1282] Wu, J.-L. C., [1643] Wu, Kun Hsiang, [1318] Wu, W. L., [507] Wu, Wen-Lan, [636] Wu, Wen-Teng, [1601] Wu, Wen, [915] Whitfort, T., [1197, 1427, 1526] Whitley, Darrell L., Yamada, Takayuki, [456] Yamada, T., [1124, 1532] Yamagata, Y., [1247] Yamagishi, M., [1862] Yamaguchi, Masashi, [1806] Yamamoto, H., [1004] Yamamoto, T., [1447] Yamamoto, Y., [1707] Yamane, Shotaro, [1728] Yamany, Sameh M., [1511] Yamashita, Katsumi, [563] Yamauchi, Toshiyuki, [359] Yamazaki, N., [1409] Yan, Wei, [1568] Yanda, Li, [1215] Yanfeng, Cheng, [1304] Yang, Jihoon, [1435] Yang, Jingfeng, [789] 946, 999, 1084] [1184] Whitley, Darrell, [951, 1137, 1149, 420, 461, 462, 463, 464, 465, 466, 467, 468, 469, 470, 471, 472, 473, 474, 475] Wicker, Devert, [667] Wu, You-Min, [1777] Wieland, Alexis P., [476] Wu, Y., [1042, 1852] Wieland, F., [1283] Xavier, A. E., [1622] Wienholt, Willfried, [477, 478] Xi, Guang, [516] Wilke, Peter, [479, 480] Xi, Yugeng, [1432] Yang, Jinn-Moon, [1863, 1201, Wilke, P., [1059] Xia, Zhi-zhong, [1837] Williams, Bryn V., [108] Xianbin, Guan, [1713] Yang, Jun-an, [739] Williams, G. J., [1491] Xiang, Cui, [1869] Yang, R. L., [1667] Williams, Tom, [1051] Xiang-Wu, Meng, [1528, 1703] Yang, Sheng-Sung, [786] Williamson, A. G., [1122] Xiaohui, Zhang, [1713] Yang, Wanhai, [647] Wilson, Stewart W., [443] Xiaoming, Xu, [1420] Yang, Won Sik, [648] Winfield, A., [1233] Xibilia, M. G., [115, 116] Yang, Xiaoqin, [561] Winkler, David A., [1391] Xie, Nan, [676] Yang, Xiaowei, [1708] Winterer, G., [1206] Xie, Weixin, Yang, Xinxing, [1706] Yang, Xiukun, [499] Yang, Y. Y., [736] Yang, Y.-S., [1836] Yang, Zi-Jiang, [1570] Yao, S., [1118] Yao, X. Q., [1088] [1060, 1063, 1627, 1784] 1123] Wise, B. M., Wolfe, William J., Won, Kyoung-Jae, Wong, F., Wong, I. W., Wong, M. H., Wong, Man-Leung, [976] Xin-hua, Li, [805] [1640] Xinmin, Huang, [1420] Xiong, Y., [481] Xu, Jinwu, [1166] Xu, Lei, [815] Xu, W. H., [1445] Xu, Wen, [1524] Xu, Zong-Ben, [42] Yap, Kim H., [521] Xuan, Q. Y., [1534] Yashioka, M., [1683] Xue, Yueju, [789] Yasuda, Keiichiro, [1062] Yabuta, Tetsuro, [456] Yasuda, Yutaka, [703] Yachisako, Y., [602] Yasunaga, Moritoshi, [1804] Yamada, S., [1839] Yau, Wei-Yun, [795] [849] [1195] [1653] Yao, Xin, [515] [1031] Wong, Y. K., [1653] Wongsarnpigoon, Amorn, [1143, 1146, 1147, 1286, 1332, 1491, 1535, 1569, 1704, 1730, 1801, 1835, 1854, 482, 483] [21] Woo, Kwang-Bang, [1319, 1331] Wood, Dan, [167] Woolley, I., [1702] 1262] [706] [913] Wong, Patrick M., Worden, K., Xin, Zhan-hong, [914, 1014, 42 Genetic algorithms and neural networks Yazgan, E., [887] Yusof, Rubiyah, [1824] Zhang, Yong, [596, 1873] Ye, Shenghua, [682] Zagorski, Peter, [830, 920] Zhang, Z. H., [1285] Yegnanarayana, B., [1477, 1557] Zak, B., [1357] Zhang, Z. J., [1345] Yen, G. G., [616] Zalesski, George, [1389] Zhang, Zhaohui, [1333] Yen, Gary G., [585] Zalzala, A. M. S., [36, 1754] Zhang, Zhixiong, [1125] Yeun, Jin Seon, [1882] Zamparelli, Michele, [1538] Zhao, Heng, [647] Yeun, Y.-S., [1836] Zamzow, Thomas, [1430] Zhao, Q. F., [1235] Yew, Liam, [528] Zanela, A., [1269] Zhao, Qiangfu, Yih, Y. W., [1088] Zecun, Zhou, Yih, Yuehwern, [1033] Zeigler, Bernard P., Yiming, Zhang, [1713] Ying, Li, [526] Yingli, Luo, [1869] Yip, Devil H., [1606] Yip, P. P. C., [952] Yip, Percy P. C., [1061] Yokoyama, Ryuichi, [1062] Yon, Jung-Heum, [1640] Yoon, Byungjoo, [917] Yoon, Seong-Sik, [1245] Yoshida, K., [630, 1680] Yoshihara, Ikuo, [1804] Yoshihara, I., [1839] Yoshimoto, Katsuhisa, [1062] Yoshimura, Motohide, [1225] Yoshino, Toshiki, [1732] Yoshino, T., [1337] Yoshioka, Michifumi, [1509, 1563] Yoshizawa, Shuji, [1227, 1801, 100] [1531] [1841] Zeng, X. Y., [1712] Zeng, Xiang-Yan, [563] Zeng, X.-Y., [573] Zervakis, M., [511] Zhang, Bao-Jin, [1878] Zhang, Bo, [1333] Zhang, B.-T., [943] Zhang, Byoung-Tak, [831, 921, 981, 1295, 1367, 1845, 80, 351, 352, 458] [1834] Zhao, Zhongxu, [492] Zheng, Bin, [1748, 1833, 1840] Zheng, Bo, [807] Zheng, Guang L., [975] Zhenya, He, [1289] Zhitong, Sui, [1234] Zhizheng, Wu, [1420] Zhong, Binglin, [702] Zhongjun, Zhang, [1325] Zhou, Chunguang, [1708] Zhang, Changli, [796] Zhou, J., [519] Zhang, Ching, [924] Zhou, Lei, [764] Zhang, D., [953] Zhou, Y. H., [1285, 1670] Zhang, G. L., [1670] Zhou, Yaohe, [1669] Zhang, G. Q., [1872] Zhou, Yuanhui, [1333, 1537] Zhang, Hai-jun, [706] Zhou, Zecun, [1524] Zhang, J. H., [519] Zhu, Zhaoda, [1568] Zhang, Jianna, [550] Zhuang, Hualiang, [795] Zhang, Jianping, [1214] Zhuang, Zhenquan, [739] Zihua, G., [1773] Zitar, Raed Abu, [1064] Zocca, L., [1126] Zuben, F. J. Von, [1766] Youkun, Lei, [1374] Zhang, Lianbao, [775] Yu, E. S., [1767] Zhang, Liang-Jie, [1138] Yu, Jung-Shik, [1319, 1331] Zhang, Liangjie, [1218] Yu, William W., [1606] Zhang, Mengjie, [1807] Yu, Zhang, [1759] Zhang, P. X., [1234] Yuan, Huang, [1778] Zhang, Qi-Zhi, [1878] Yuanping, Ni, [1710] Zhang, Qizhi, [1669] Yubazaki, N., [61] Zhang, Yan-Qing, [1350] Zhang, Yonghuai, [1873] Yunes, Adolfo González, [486] Zhao, Xiao-Wei, [1010, 1202, 1317] Zelinka, Ivan, [1236, 1338, 1342, 1488] Zuben, Fernando J. Von, [669, 725] Zuo, Kewei, [1601] Zurada, J. M., [601] total 1870 articles by 3144 different authors Subject index 4.7 43 Subject index All subject keywords of the papers given by the editor of this bibliography are shown next. 2D GA, [1040] 2Delta-Gann, [868] adaptation, [529] adaptive filters neural networks, aerodynamics, [1134, 1141] angiography Baldwin effect, [977, 1767] [731] bandwidth allocation, [1458] animation, [1102] Bayesian networks, [1364] animats, [167] beams Anna Eleonora, [319] fluorescein, [460, 692] ant systems, [679] airfoil, [684] antennas, [1886, 1871] aerospace, [401] ants flight control, agents, [550, 1486, [1489] neural networks, [483, 970, 1860] neural networks and GA, C. niger, [872] buckling, bibliography Aplysia, [654] [299] special, [410] [1860] biochemistry 1562] application neural network, [1627, 1692] neural networks, [583] agriculture, military, [449] [302, 1768] agriculture applications fruit storage, [1476] fruits, [1556] business, [292] industrial, [1792] greenhouse control, [1694] [803] clean up, nitrogen, art, [838] [1480] artificial intelligence, [733, 796, 803] weed detection, [723] air pollution [51, 1775, 1790] cognition, [54] artificial life, [139, 148, 89, 158, 958, 959, 525, 662] forecasting, [747, 761] insect, [1636] neural networks, [782, 792] analysing GA continuous space, Hebb-rule, training physiology, [1369] biosensors, [1656] biotechnology, [1207, 1601] blind source separation, [640] Boltzmann machine, neural sunspots, [1186, 1212] time series, [551] networks, Markov chains, [42] ATM, [1759] mutation, [50, 732] automata, [96] mutation rate, [42] mutations, [1784] parameter tuning, [773] population size, [42] selection, [41, 50] Boolean, [310] [1887], [784] autonomous vehicles, [661] brain hemodynamics, breeder GA, [58] [831, 921, breeding, [831] brewing, [1821] [271, 1052, 1198, 1249] VLSI, calibration, spectroscopy, CAM, [929] [107] [799] [985, 1249] cancer automotive body welding, [95] book review CAD, [488] [1485] [1467] [1194] astronomy in [1654] 1487] [42] filters, mate preference, [409, 1424] [55] diversity, [1415] [24, 27] associative memory, convergence, evolution, modeling, [776] tomato, [1697] [1130] artificial brain, robotic, peptides, biology [1738] [776] remote sensing, [807] bioprocess aquifer hydroponics, pathogen bacteria, [971] breast, [1377, 1725, 1833, 518, 755] brest, [637] detection, [1148] 44 Genetic algorithms and neural networks diagnosis, [755] melanoma, [1364] CANFIS, [67] carbon flux, [789] text, [1767] classifier fuzzy, [127, 328, 300, 948, 1686, 599] neural networks, [1668] [90, 112, 382, 1057, 1278, 1362, 1712, 1857, 1859] [586] cellular automata, [958, 959, character recognition, [1041] 985, 1404, 535] neural networks, [1527] channel routing, [764] chaos, chemical data, [654] chemical process, [1616] chemical reactions modeling, [612] [807] analytical, [1501, 547, chromatography, [992] [795] linear controllers, [1126] piece-wise linear, [1255] neural network, [889, 764] classsifiers, [1157] neural network learning, cluster analysis, [1647] neural networks, clustering, [137, 295] regression, chemometrics, [976, 572] red wine adulteration, voltammetry, [768] [715] chromosome long, ciphers, [283, 302, 976, 994, 1126, 1237, 1364, 1484, 1496, 1580, 1686, 1709, 731, 731] [711] nonlinear regression, [976] co-evolution, [1230] Powell’s method, [354] coding, [228] quasi-Newton, [1676] atomic, diploid, recombination schemes, [1160] [1035] simulated annealing, [1525] [354, 1109, 1126, 1359, 1502, 1815] real, [1538, 575] statistical methods, [1484] set based, [1257] statistical models, [1020, 1135, 1488, 1585, 1757, 1774, 1782, 529, 755] structural, [1261, 1275, 1320, 1330, 1446, 1868] [194] [1521] [743, 754] [855] [989] neural networks in protein secondary structure prediction, [1865] coevolution, physical, [1881] neural networks, neural net applications, [1780] organic, in regression, [548] Levenberg-Marquardt, 654, 713] cement, [1630] [289, 1815] in nuclear engineering, clusters chemistry analytic, in neural network design, [1674] [1547, 1572, 741] [604] neural network, [838, 1538] channel assignment, [1748, 1840] in neural networks, [1608] classifiers, CBMS, in diagnosis, in neural network training, [1254] cardiology imaging, [1126] in medical data mining, [1063] classifier systems, in control, learning, cognition, testing, [1235] complexity, impeller design, computer graphics, [58] computer science [490] [457] compressor [54] combustion, [1787] operating systems, [516] [1383, 1443] [835] coal, [642] computer-aided design, [1052] [1096] NOx, [642] control, [1154] comparison, [1230] classification, [345, 1014, 1121, 1230, 1446, 1511, 499, 511, 529, 540, 605, 694, 757] comparison control parallel methods in TSP, [12] cost-sensitive, [1435] back propagation, forest, [781] backpropagation, adaptive, [927, 1283, 1573] comparison classification [89, 246, 448, 460, 882, 899, 932, 963, 971, 1057, 1065, 1328, 1408, 1633, 617] chaotic systems, [1387] cooling, [532] flight, [520] flight?, [1119] force, [1145] [354, 1220] [989, 1109, 1672, 546] handwritten characters, [579, 644] fuzzy logic, [1709] images, [1314] linear, [644] neural networks, [1687, 773] human, [787] rules, [1358, 1596] in classification, [731] GA better than neural approach, [1686] fuzzy, [960, 1010, 1145, 1283, 1880, 1368, 1460, 1463, 1515, 1642, 1694, 1701, 1776, 532, 722] Subject index 45 genetic programming, [43] inverted pendulum, [1614, 1683] robot, [45, 704] controllers, [114, 180, decision support systems, decision trees, [538] [1836] 263, 340, 1700] laser, ID3, [39] fuzzy, locomotion, [1636, 1741, 1742] [927, 1092, 1202, 1226, 34, 1317, 1662, 1824, 487] [417] delta-sigma modulation, [744, 759] design, [525] machining, [1319] neural, manipulator, [861, 1340] neural network, manipulators, [52] manufacturing, [1088] mobile robot, [1861] model predictive, [1676, 1702] motion, [1102] controllers 7robust, [1822] neural, [1720] convergence, [29] cancer, [1833] coodbook design, [1506] cardiac disease, [67] cooperation, [14] diabetes, [731, 731] failure, [540] neural network, [951, 1547, 1636, 1640, 1667, 1693, 1760, 704, 734, 758] neural networks, [843, 1420, 1799, 1822] neuro, [61] [1039, 1163] [1279, 1348, 1741, 1809, 1812, 592, 677, 710] neural networks, [1178, 1497] PID, [965, 1509, 1683, 1756] robot, prisoner’s dilemma, [1617] crack identification, [566] criminology, [1083] [691] optimal, [1663, 1689] power, [1691] cycle, power system, [1728, 1735] diversification role of, power systems, [570] [1075, 1325, 1428, 1663, 1825, 664, 740] [27] tracking, [1331] truck backer-upper, [949] vehicles, [1818] cutting, data analysis, [691] [87, 1876, 1406] selection, DNA, DNA sequencer, data mining, [584] dynamical systems, feature selection, [1778] medical, [604] databases [1015] queries, [1329] retrieval, [833] 1742, 1799] datamining, [632] decision, [1875] [623] [721] [41] [718, 738] [997] [855, 1697, [1307] dynamics chaos, [1288] urban design, [728] ECG, [1516, 1786] P wave, [1830] ecology freshwater, [591] remote sensing, [797] economics [205, 206, decision making accounting, control/neural network, [1536] [724] [1697, 1868] coding regions, 544] vibrations, 207, 358, 456] mutation, [628] drug design, [1537] control systems, differential evolution, [284] knowledge, control robot, aircraft engine, data fusion, [1737] [1409, 1512, [549, 616] [274, 1487] vibration, walking, [221, 300, 1583, 1650, 1825, 554, 562, 688] diversity, [1571] [1552, 615] fault, [296] current transients, [1202] [873, 1124] diploidy, [1381] temperature, diagnosis, [1534] [517] cultural algorithm, system identification, fault, unimodal normal, [1741] [1133, 1686] [731] [283] reptation, rule based, retinopathy, permutation, [1154, 1352] [1828] [731] diagnostics [283] cryptology, robust, retinal images, [435, 938, 1624] [168] [840, 1316, 1322, 1682, 734, 762, 765] diabetes medical, crossover, process control, robot, [696] diagnastics [525, 600] non-linear, process, conceptual, urban planning, [972] [728] bankruptry prediction, controller decision support, [1464, 700] 1278] [1156, 46 Genetic algorithms and neural networks credit evaluation, [1518, 1884] EMG, [345] radio, [62, 1568, 1886, 526, 1871] currency trading, enegineering [293] structural, exchange rate forecasting, [126] exchange rates, [1817] finance, [972, 31, 1305, power, [914, 1015, 1237, 1489, 1566, 1649, 1729, 1737, 1827, 553, 599, 656, 779] [379] energy enginering solar, [794, 809] wave, [59] 1580, 700] financial prediction, [1678] financial time series, [763] engineering [375, 460, 843, 926, 1879, 1119, 1202, 1222, 1668, 516, 537, 602, 609, 628, 655, 684, 692, 696, 721] [1445] market behaviour, [1483] markets, [614] bio, portfolio selection, [13] bio-, prediction, [1297] project management, [1798] [449] chemical, chemistry, sales forecasting, [621] civil, stock market, [1398] stock markets, [674] [134, 294, 135, 1445, 53, 16, 652] [417] economics?, [18] economy [459] edge detector, [716] editorial, [28] EEG, [1206] electromagnetics, [450, 1101, 1667, 1727, 1738, 1793, 1798, 1872, 735, 794] control, [740] electrical, [1277] electronics, [201] energy, [59, 809] geotechnical, [714] machine, [1430, 1641] material, [894] materials, [1827, 701, 736, 779, 784, 785, 788] [1583] medical, [376] [1878] metallurgy, [839] municipal, [306] [1205, 62, nuclear, [1886, 1871] petroleum, electronic nose, [265] power, electronics, [1829] digital, [535, 571] manufacturing, [659, 752, 756] manufacturing, [1327] [1500] elitism, [1538] embedded systems, [835] emergence, [529] [548, 220, 221, 1124] [1603] silicon processing, [1670, 736, 775] electromyogram, semiconductor environment pollution, [735] environmental science, [1857] ENZO, [1041, 1301] ENZO-II, [920, 920] ENZO-M, [830] estimation, [873, 1666] ethology, [299, 850] evolution, [22, 1172] ESS, [1415] optimization, [1423] evolution strategies, mechanical, 484, 523, 653] antennas, [1195] [1762] [425, 103, 26, 1220, 1424, 1549, 1562, 1576, 1664, 1746, 525, 529, 581, 582, 645] evolution strategies [14] Edelman, ei GA?, [1664] evolution programming, [525] economics modeling, EGY, [1325, 1739, 612] [15] trading, [1416, 1601, 1663, 1689, 1821] risk, artificial, misfire, aerospace, forecasting, structural, engines [732] neural networks, [264, 477, 478] evolution strategies?, [1372] evolution strategy, [852] evolutionary computation, [25] evolutionary programming, [187, 190, 331] evolutionary strategies, [827, 919, 998, 786] evolvable hardware, [508, 535, 569, 571] [620] [221, 300, 856, 873, 874, 956, 1038, 1057, 1062, 1094, 1105, 1253, 1265, 1284, 1294, 1308, 1326, 1343, 1361, 1374, 1390, 1397, 1466, 1479, 1499, 1524, 1530, 1531, 1534, 1536, 1539, 1545, 1571, 1583, 1602, 1612, 1634, 1644, 1653, 1691, 1709, 1715, 1728, 1735, 1740, 1762, 1776, 1802, 1828, 1850, 1853, 490, 498, 1864, 1867, 554, 555, 560, 1869, 570, 602, 618, 628, 642, 648, 687, 688, 732, 794] FPGA, [802] self-replicating, [501] experimental design, Taguchi, expert systems, [957, 1345, 1467, 1601, 1689, 1690, 1821, 620, 722] [1207] [58] [553] [1448, 494, 775] fuzzy, [1108, 585, 616] face recognition, process, processs, mutation, fault detection, [308] [1014, 1174, 1386, 1615] motor, [560] Subject index fault tolerance, feature extraction, 47 [1545] [431, 1781, FPGA, neural networks, [1804] 100, [361] [802] 1000, [1538] [1598] 30, [1435] [731] 300-600, [525] [1556] 50, [1593] 511] fractals, feature selection, [1358, 1596, image analysis, 1610, 1767] fuzzy, [627] fruit treatment, features, [1782] fruits FEM, [1745, 553] mesh generation, fermentation, sake, filters, [1566] cherries, fuel additives, [499] [490] [1663, 722] FuGeNeSys, [1658] [1416] fuzzy classification, [1427] [565] fuzzy logic, adaptive, [365, 539] electronic, [1448] morhological, [1814] morphological, [729] neural networks, generators [365] finance forecasting, identification, partial, genetic programming linear, tutorial, [174] neural networks, genetics [109, 950, gene-gene interaction, 1015] fitness function, neural network, [844] GENNET, [322] GenNETS, [146, 153] [1280] [797] geology, hybrid, [445, 632] geophysics learning, [832] neural network, [67] [1620] [1238] [1299, 1355, [721] neural networks, [1658, 1726, 532, 804] seismology, [1819] gephysics hydraulic conductivity, [1838] GESA, [952] [1051] GINN, [1501] GA-ANNE, [789] GIS game theory, [850] review, queries, GOLEM, games food [727] GENIAL, classifiers, 1543] fluid dynamics, [176, 206, 207, 208, 312, 967, 32, 1214, 1283, 1436, 1792, 603, 615, 658, 709, 755, 767] fuzzy systems [1310, 1335, [826, 851, [593] fuzzy sets, [1083] [692] [604] 1388, 1677] [1183] 1337, 1732] royal road, [548, 278, 297, 217, 218, 351, 447, 930, 1184, 1309, 1495, 1504, 43, 1580, 1590, 48, 1675, 1765, 1836, 1846, 1856, 1858, 491, 14, 508, 569, 713, 727] [1719] fuzzy reasoning, [285] genetic programming, reasoning, [1407] fitness neural networks, GENESIS, [444, 1071, 1197, 1250] fuzzy systems, finger prints, winding protection, [1583] fruits, [499] checkers, [1744, 661] plant oil, [799] computer, [1481] [1329] [569] grammars attribute, [1810] red wine, [768] Go, [1671] gray fish, storage, [1101] Othello, [347, 925] GRNN, [637] food processing, [693] othello, [1077] groundwater, [306] Othello, [595] habituation, [214] food quality defects, [499] prisoner’s dilemma, [1617] peanuts, [496] Tron, [1585] [1621] GANNET, [308, 833] power, [555] GANNet, [845] power load, [1466, 1602] GANNFL, [1250] sales, [621] GBFNN, [1412] time series, [668] generations forecasting, [439] handwriting Arabic, [1351] hardware evolvable, [1227, 1274, 1450, 1775, 1848, 512] FPGA, [729] HDGA, [1202, 1317] health monitoring, [376] 48 Genetic algorithms and neural networks Higgs boson, [672] control, high energy physics, [87] hydropower, [1057] hill-climbing, [33] ID3, [417] [1511] IKONOS, cancer, [1725] image processing, histology?, [1082] histology, Hopfield neural networks, hybrid, [301, 1357] [1877] fuzzy, [927, 1005, 1645, 1724, 1794, 1849, 530] [781, 797] [328, 109, 212, 23, 841, 901, 907, 908, 924, 950, 1041, 1043, 1879, 1161, 1293, 1376, 1681, 509, 716] classification, neural networks, [1006, 1086, 1437, 796] [725] implementaion hardware, [512] implementation C, [197] C++, [284, 327, 1025] Cde*, image processing Connection Machine, [440] [440] Cray Y-MP8/864, [271, 858] clouds, [1484] DSP, [1396] color, [1832] [1128, 1244] fuzzy logic, [59] Fortran 77, [1697] GANNFL, [1250] compression, [1434] FPGA, [795, 798] gradient method, [1834] edge detection, [561] hardware, [1227] immune systems, [647] feature extraction, [431] MATLAB, [882] local search, [855] filtering, [1538] MIMD, [855] neural netoworks, [1849] filters, [510] Paragon XP/S 10, [1538] fuzzy, [1395] parallel, [720] handwriting, [1004] PLD, [1227] medical, [1725, 589] PVM, [1273] neural networks, [1125, 729] quantum computer, [800] noise cancellation, [1769] transputer T800, [197] transputers, [311, 829] Verilog, [810] VLSI, [1870] XROUTE, [286] neural network, [833, 1076, 1103, 1280, 1283, 1334, 1578, 1641, 1669, 502, 613, 659] neural networks, [550, 433, 817, 841, 881, 891, 894, 901, 904, 908, 909, 914, 927, 929, 931, 946, 949, 984, 999, 1003, 1005, 1009, 1014, 1030, 1033, 1055, 1062, 1084, 1088, 1108, 1128, 1151, 1154, 1167, 1171, 1202, 1209, 1231, 1240, 1244, 1279, 1294, 1317, 1329, 1336, 1357, 1411, 1415, 1446, 1459, 1481, 1490, 1530, 1544, 1545, 1566, 1568, 1582, 1584, 1585, 1592, 1598, 1601, 1603, 1643, 1645, 1649, 1666, 1670, 1707, 1724, 1733, 1745, 1759, 1768, 1777, 1792, 1794, 1816, 1837, 1838, 488, 490, 516, 526, 530, 537, 551, 553, 566, 571, 602, 611, 617, 618, 628, 642, 669, 674, 684, 692, 696, 706, 714, 716, 728, 736, 750, 752, 756, 763, 766, 776, 779, 784, 788, 789, 793, 797, 798, 799] pattern recognition, [934, 1153, 1209, 1244, 1246, 1335, 1351, 1370, 1882, 1513, 1721, 808] recognition, [1013] remote sensing, [1768] remote sensins, [1712] restoration, [1311, 521] incremental evolution neural networks, inference segmentation, [66, 492, 705, fuzzy, 723] quantum computing, [739] shape identification, [1533] information retrieval, quasi-Newton, texture, [1225] infrared imaging, [990, 1210] inheritance [1218] simulated annealing, [354, 1882] image processing?, softcomputing, [632] imageprocessing SOM, [742] support vector machine, tabu search, noise removal, [806] [1552] fuzzy, Lamarckian, [565] IR, [1768] [1210, 1608, 1719, 589] [1103] hydrid simulated annealing, [564] initial population, [648] [1717] [1768] [533, 574] [285] insects imaging medical, hybris [582] ants, insulation, [654] [1277] integer programming multispectral, [499, 797] remote sensing, [1314] interval arithmetics, inverse problems nonlinear, [1733] [354] thermal, [1768] hydro power, [379] ultrasonic, [1608, 1719] damage, [779] hydrodynamics, [460] immune systems, [753] electromagnetics, [1205] Subject index seismology, 49 [1819] isolation, [296] ITA, [1615] machine learning, [504, 402, 121, 215, 350, 367, 368, 80, 271, 123, 979, 1226, 1231, 1235, 1242, 1285, 1289, 1346, 1368, 1435, 1454, 1459, 1475, 39, 1521, 1569, 1582, 1585, 1674, 1686, 1744, 1757, 1791, 1852, 491, 56, 584, 595, 599, 632, 707, 755, 763] jet engines performance estimation, Kanerva’s memory, Khepera, knowledge aquisition, machine learning [165] [731] control, [740] decision, [1127] ECG, [810] [1427] [1197, 567] [1435] Kohonen feature maps, [388] Kohonen methods, classification, [623] knowledge based systems, knowledge discovery, [602] [877] Kohonen nets, [235, 100, fuzzy, 17] neural network, neural networks, 1783, 598] [1239] [194, 951, 597, 629] L systems, [1426] laminates, [656] machine learningi, land mines, [1768] machine vision, rules, walking, plasma etching, [1670] quenching, [775] sintering, surface melting, macromolecules, [1558] standard cell, [1331] [732] [1038, 1612] short-term, [1253] [1773] marketing, [1471] materials, [1234] aluminium, [736] heat treatment, [609] [785] mathematics regressions, medical imaging, [1073] [1399] [1376, 1511, 1725, 66, 492] [1788] radiographs, [1232] retina, [731] fault detection, [1361] tomography, [820] leak localization, [1268] ultrasound, [705] predictive, [585] medical imaging?, [62] maize, [776] medicine, [418] mammography, [1376] alcoholics, [1206] [1835] anesthesia, [540] cancer, calibration, [1264] decision support, [836] single link, short term, maps?, MRI, [1364, 1377, 1881, 1554, 1725, 1833, 1835, 518, 754] cardiology, [1516, 1719, 641, 67] [856, 1466, 1602, 1796] [785] [1391] manipulators load forecasting, turning, QSAR, [1544] load forecast, [1670] [58] [1530] [145] surface treatment, fMRI, [283] LIZZY, [534] [1521] management linear programming, sintering, proteins, diagnosis, line loss, [701, 784, 788] [637] [929] Lin-Kernighan algorithm, sheet metal, cancer, [1025] [1054] [1641] [1275, 1446] [1593] LGANN, [805] rolling mill, [1697] [1669] [437] rapid prototyping, peptides, [805] learning, [682] max cut, maintenance layout design, quality, turning force, [256, 257, lattice model 128mer, [1252] materials processing machining manufacturing, production, [137] [1201] lasers [1319] [1590] 1269, 499] languages regular, [1060, 1123, plasma etching, consultation system, [865] [861] dentisry, manufacturing [530] diagnosis, logic [1569, 1719, 1748, 1840, 518, 605, 731] annealing, [609] control, [502] EMG, [345, 1231] multiple-valued, [1707] laser ablation, [752, 756] gait, [507] reasoning, [1707] laser processing, [775] genetics, [727] [1021] moulding, [624] geriatry, [605] LVQ, 50 Genetic algorithms and neural networks hemorrhagic blood loss, [1626] composition, hepatology, [1777] music composition, [386] histology, [1148, 511] mutation, [910] mammography, [1210, 1748, adaptive, wavelet, [1543] neural networks, [1785] 1840] deterministic, neurology, [1231, 1358, 1596, 63, 495, 645, 58, 787, 21] ophthalmology, [731] orthopediatry, [787] orthopedy, [636] prediction, [1173] signal processing, [1786, 65] sleeping, [100] surgery, [49, 540] vision, [68] [1335, 1337, 1651] dynamic, [1129] trigonometric, [721] mutation rate 0.001, [1435] mutations Cauchy, [1784] deterministic, [1472] Gaussian, [1784] mutattion melanoma, [1554] neural network controlled, messy GA, [1785] [268, 1163, nanotechnology 1226] meta GA, [197] meteorology, [165, 1360] thin films, [791] navigation clouds, [1484] indoor, [811] estimation, [1469] robot, [1813, 1861] microbiology, [693] neural Darvinism, [1486] microscopy, [1437] neural Darwinism, [1519, 1790] MIMD, [393] neural netiworks mobile robot, [1190] mobile robots, [240, 241, 313] model identification, [1455] modeling perceptrons, neural netorks evolution, [1152] neural netowork, [821] [1072] materials, [788] neural netoworks, soil, [714] neural network, Monte Carlo, [1593] motion control, [272] [819] [812, 818, 916, 1271, 1487, 1579, 505, 794] complex, [782, 792] control, [1428, 765] design, [1310] motor electrical, [560] fuzzy, motors [1289, 1350, 1786, 1806, 765] electric, [1545] image processing, induction, [1284] pattern recognition, [556] reluctance, [1361] PCA, [1674] moulding, [624] rule extraction, [1333] multiplexer problem, [303] signal processing, [1121] multispectral imaging, [729] structure selection, [996] music, [1299, 1592] training, [1200] [795] [1118] [548, 665, 703, 96, 163, 164, 426, 454, 74, 75, 128, 129, 230, 287, 303, 461, 462, 76, 82, 90, 118, 127, 132, 133, 213, 231, 232, 328, 364, 421, 463, 464, 465, 466, 467, 468, 77, 83, 87, 92, 111, 114, 122, 138, 140, 141, 142, 143, 144, 161, 165, 170, 179, 180, 181, 182, 183, 184, 185, 186, 222, 224, 233, 260, 261, 266, 268, 272, 285, 286, 289, 290, 291, 304, 317, 322, 342, 377, 384, 385, 390, 393, 402, 415, 419, 422, 434, 437, 443, 455, 469, 470, 85, 95, 97, 99, 105, 107, 120, 121, 136, 139, 145, 146, 147, 148, 149, 159, 162, 167, 175, 187, 188, 189, 195, 214, 215, 234, 239, 262, 267, 298, 308, 311, 320, 324, 350, 367, 368, 369, 372, 386, 394, 397, 398, 423, 425, 427, 435, 451, 458, 471, 472, 476, 68, 69, 70, 80, 81, 88, 91, 93, 98, 112, 113, 115, 119, 125, 134, 150, 151, 169, 171, 172, 173, 190, 191, 192, 198, 202, 217, 218, 220, 221, 225, 226, 227, 228, 229, 236, 237, 240, 241, 242, 243, 244, 245, 270, 271, 279, 280, 284, 288, 294, 296, 306, 307, 313, 316, 321, 325, 326, 329, 330, 331, 332, 337, 343, 344, 345, 346, 354, 355, 366, 380, 387, 391, 392, 412, 417, 420, 429, 432, 436, 439, 440, 457, 473, 474, 481, 482, 71, 72, 73, 86, 89, 94, 106, 108, 109, 110, 116, 117, 123, 135, 152, 153, 154, 155, 160, 166, 168, 176, 178, 193, 196, 200, 203, 205, 206, 207, 208, 211, 246, 247, 248, 249, 250, 251, 252, 253, 254, 255, 256, 257, 265, 269, 274, 275, 276, 281, 282, 292, 300, 305, 309, 310, 312, 314, 315, 318, 319, 333, 335, 340, 341, 348, 351, 353, 357, 358, 359, 360, 370, 371, 374, 376, 378, 379, 381, 382, 383, 388, 395, 400, 404, 405, 406, 407, 413, 416, 418, 430, 441, 444, 446, 447, 448, 449, 450, 452, 453, 456, 459, 460, 477, 479, 483, 820, 824, 825, 828, 836, 838, 852, 853, 856, 864, 878, 879, 891, 898, 900, 902, 907, 912, 920, 923, 925, 928, 930, 932, 933, 934, 939, 942, 943, 944, 947, 948, 953, 957, 958, 959, 960, 963, 967, 968, 971, 974, 978, 979, 988, 990, 992, 1002, 1012, 1013, 1015, 1016, 1018, 1020, 1023, 1036, 1039, 1041, 1045, 1052, 1056, 1057, 1061, 1067, 1069, 1070, 1071, 1073, 1079, 1086, 1091, 1093, 1097, 1099, 1101, 1102, 1104, 1105, 1110, 1114, 1115, 1129, 1130, 1131, 1137, 1140, 1156, 1160, 1161, 1162, 1165, 1172, 1174, 1181, 1194, 1195, 1197, 1198, 1201, 1207, 1210, 1220, 1228, 1230, 1233, 1234, 1245, 1250, 1252, 1255, 1256, 1258, 1264, 1265, 1268, 1273, 1277, 1291, 1293, 1306, 1307, 1314, 1319, 1320, 1323, 1324, 1326, 1327, 1332, 1343, 1345, 1211, 1346, 1353, 1354, 1363, 1366, 1376, 1378, 1381, 1383, 1385, 1386, 1387, 1391, 1399, 1402, 1403, 1407, 1408, 1413, 1419, 1429, 1432, 1436, 1448, 1450, 1453, 1455, 1457, 1458, 1461, 1464, 1469, 1471, 1472, 1473, 1475, 1478, 1486, 1491, 1495, 1518, 1519, 1525, 1534, 1539, 1540, 1544, 1561, 1563, 1581, 1595, 1599, 1604, 1617, 1624, 1626, 1632, 1634, 1637, 1638, 1642, Subject index 51 1644, 1653, 1657, 1660, 1663, 1664, 1685, 1688, 1690, 1698, 1704, 1708, 1717, 1729, 1734, 1737, 1738, 1739, 1744, 1748, 1750, 1752, 1762, 1773, 1775, 1780, 1781, 1787, 1795, 1796, 1797, 1800, 1802, 1805, 1813, 1819, 1821, 1829, 1831, 1836, 1840, 1842, 1844, 1845, 1848, 1850, 1855, 484, 491, 495, 496, 498, 500, 501, 506, 512, 514, 519, 520, 522, 529, 531, 535, 536, 538, 542, 544, 545, 552, 568, 570, 572, 573, 574, 668, 577, 581, 587, 590, 599, 603, 608, 609, 614, 615, 619, 625, 633, 635, 646, 651, 652, 653, 655, 658, 670, 673, 676, 678, 681, 685, 687, 688, 689, 690, 697, 707, 708, 711, 713, 718, 733, 738, 751, 755, 757, 773, 774, 775, 785, 803, 805, 809] classification, [816, 1006, 1157, 1278, 1285, 1315, 1358, 1392, 1422, 1427, 1435, 1437, 1516, 1559, 1596, 1605, 1608, 1609, 1610, 1622, 1674, 1712, 1719, 1725, 1753, 1767, 1779, 1835, 524, 540, 637, 641, 683, 694, 695, 730, 743, 754, 768, 781, 783, 796] dynamic, [1825] dynamic systems, [966] Edelman, [277] electronic nose, [1037, 1747] Elman, [560, 562] classificationmachine learninf /unsupervised, [1665] ethology, [850] evolution, [493, 1127] classifier, [626, 647] classifiers, [1219, 1782] clustering, [1024, 1373] clustring, [373] CNN, [124] adaptive resonance, [1355] coding, [1184, 580] fault tolerance, [837] age, [1032] coevolution, [1722, 485] feature detection, [541] analysis, [1214] cognition, [1423] feature extraction, [511] comparison, [857, 1389] feature selection, [1406, 1507] configuration, [1074] feature vector optimization, [887] artificial intelligence, [1077] configurtation, [975] feed forward, [1778] associative memory, [1550] connection weights, [1438] feed-forward, [1493] back propagation, connectivity, feedforward, neural networks architecture, [84, 854, 1007, 1482, 1684, 594, 780] [1249, 808] evolution strategies, [477] evolutionary, [336] [1287] evolving, [1655, 1854, 586] fault detection, [1166, 1715, 1740, 560, 680] [941, 1221, 1266, 1466, 1477, 1489] back-propagation, [1417, 786] backpropagation, [880, 885, 935, 1203, 1313, 1526, 1590, 1618, 1672, 1839] Baldwin effect, [977] Bayes, [584] Bayesian, [995, 1182, 1456, 1833, 679] construction, [847] contro, [1742] control, [273, 401, 424, 475, 840, 843, 869, 872, 892, 899, 926, 964, 1001, 1008, 1010, 1011, 1049, 1064, 1092, 1112, 1117, 1119, 1133, 1226, 1270, 1284, 1290, 1325, 1331, 1368, 1409, 1414, 1416, 1420, 1421, 1451, 1460, 1463, 1476, 1508, 1509, 1512, 1515, 1520, 1556, 1558, 1562, 1565, 1573, 1614, 1628, 1676, 1680, 1682, 1683, 1689, 1694, 1700, 1702, 1720, 1735, 1746, 1749, 1754, 1756, 1758, 1818, 1823, 1828, 1856, 1858, 508, 569, 600, 675, 691, 720, 722, 746, 767, 787] bibliography, [1860] binary logic, [1532] biological, [299, 1369] biomimetic, [712] controllers, [263, 897, 965] Boltzmann, [886] cooperation, [1736] Boolean, [219] crossover, [938] BP, [1710] data mining, [604, 682] brain, [1790] decision, [1379] breeder GA, [831] delayed reward, [517] CA, [1404] cascade correlation, [1521] cellular, [950, 1168, 1269, 1538, 1652, 558, 589] cellular automata, [157, 985] cellular automata, [158] chaotic, [1763] design, [278, 338, 339, 411, 827, 861, 866, 873, 884, 895, 919, 945, 991, 1068, 1078, 1095, 1139, 1147, 1199, 1251, 1266, 1295, 1316, 1337, 1340, 1394, 1400, 1425, 1513, 1613, 1648, 1687, 1730, 1732, 487, 509] diagnosis, [982, 1262, 1479, 1524, 1531, 1583, 1615, 1650, 518] DSP, [1801] filters, [1029, 1134, 1141] fitness, [352, 1238, 1543] forecasting, [126, 874, 1390, 1439, 1602, 1612, 1621, 1817, 700, 747, 761] FPAA, [772] FPGA, [623, 760, 769, 772, 795, 810] fuzzy, [131, 216, 204, 817, 1010, 1090, 1138, 1145, 1188, 1203, 1215, 1318, 1328, 1351, 1372, 1395, 1397, 1401, 1412, 1441, 1467, 1523, 1548, 1551, 1575, 1577, 1616, 1633, 1659, 1662, 1691, 1701, 1706, 1713, 1766, 1769, 1776, 1824, 1830, 494, 510, 523, 534, 539, 549, 565, 585, 593, 621, 627, 648, 649, 660, 709, 723, 737] fuzzy logic, [1059, 643] fuzzy rules, [1089, 1699] game of life, [790, 801] games, [347, 1671, 595, 661] generalization, [829] generalizations, [846] genetic programming, hardware, [491] [1227, 1546, 802] Hebbian, [1541] 52 Genetic algorithms and neural networks hierarchical, [521] modular, [1498, 1535, regression, [1635, 791] 543] review, Hopfield, [301, 918, 1043, 1158, 1205, 1352, 1357, 1424, 1431, 1528, 1572, 1703, 527, 559, 561] hybrid, [445, 913, 984, 1033, 1054, 1065, 1098, 1259, 1261, 1275, 1330, 1362, 1494, 1501, 1593, 1692, 1697, 1711, 1733, 1798, 596, 624, 632, 636, 766] identification, [1034, 1222] image processing, [431, 1082, 1153, 1225, 1370, 1434, 510] image segmentation, [1788] implementation, in control, [327, 1468] [1027] monitoring, [1430] RNA folding modeling, [762] rule based, [634] rule extraction, [630] motion planning, multistrategy learning, [156] mutation, [1651] navigation, [811] optimisation, [686, 1492, 612, 715] optimization, [209, 830, 839, 849, 893, 918, 941, 973, 1046, 1142, 1144, 1188, 1193, 1212, 1218, 1305, 1695, 1793, 1815] [1296] [1770, 1847] input selection, [375, 1360] inverse problems, [701] inversion, [513] knowledge, [865] rules, [1155, 1827] scheduling, [130] self-organizing map, [1229, 1594, 1716, 1731, 1857, 1859] sensoring, [1217, 1656, 1772] sequential, [911] parallel, [480] sigma-phi, [921] parameters, [1474] signal processing, Pareto, [1727] patent, [620] pattern matching, [356] [582] initialisation, rule extraction.classification /rule based, [1673] [361] [1322] incremental evolution, [1081] optoelectronic, in image processing, [1311] incremental, [414, 834, 867, 871, 983, 1051, 1151] modularity, [1030, 1570, 1571, 640, 739, 744, 759] simulation, [645] SOM, [515, 1272, 1506, 1510, 1647, 1791, 555, 557, 598, 616, 638, 783, 797] pattern recognition, [940, 1004, 1136, 1179, 1183, 1243, 1246, 1267, 1335, 1396, 1449, 1511, 1606, 1611, 1681, 1721, 1810, 1814, 564, 579, 605, 610, 644, 657, 672] Kohonen, [235, 100, 863, 1000, 1060, 1123, 1308, 1761, 1783, 1791, 492, 742] L-system, [1607] lean, [1223] learing, [1454] perceptron, [1239, 1253, 654, 729] perceptrons, [409, 258, 259, 936, 1038, 1066, 1180, 1196, 1301, 1312, 1588, 1589, 1623, 1751, 1774, 1808, 578] [1480] power engineering, [956] prediction, [699, 1031, 1206, 1297, 1367, 1440, 1483, 1678, 1743, 1834, 726] process control, [1075] pruning, [1113, 693] quantum, [1405] learning rate, [1618] radial basic function, learning rules, [396] radial basis, [1303] [1080] radial basis function, load forecasting, [1374] LVQ, [349, 1021] machine learning, [1569, 1851] radial basis functions, massive, [158] RBF, medical applications, [1146] [895] structure, [671, 297, 102, 104, 103, 212, 334, 876, 882, 910, 937, 952, 1028, 1035, 1040, 1090, 1111, 1120, 1159, 1163, 1173, 1187, 1191, 1204, 1217, 1260, 1274, 1300, 1426, 1462, 1505, 1522, 1553, 1587, 1591, 1597, 1619, 1629, 1661, 1757, 1771, 1826, 497, 499, 525, 543, 580, 650, 717, 727, 732, 771] support vector machine, [806, 807] planning, learning, [504, 137, 438, 442, 815, 210, 823, 835, 858, 860, 885, 890, 903, 906, 915, 962, 969, 981, 1042, 1058, 1135, 1180, 1187, 1189, 1190, 1192, 1215, 1224, 1235, 1236, 1242, 1247, 1257, 1260, 1286, 1300, 1313, 1338, 1341, 1342, 1344, 1347, 1359, 1371, 1410, 1418, 1488, 1504, 1514, 1537, 1554, 1600, 1620, 1631, 1639, 1675, 1703, 1755, 1758, 1789, 1841, 503, 533, 567, 588, 606, 629, 649, 719, 740, 748, 753, 1861] sparse, [870, 975, 1063, 1281, 1282, 1302, 1341, 1344, 1452, 576, 749] [1216] [1365, 1465, 1542, 1560, 1616, 1679, 1702, 1852, 666, 777] memory, [848] RBF networks, model, [1339] recurrent, modeling, [1361, 1500] [1026] [954, 1019, 1094, 1176, 1248, 1288, 1447, 1621, 1696, 1714] support vector machines, survey, [698] [1213] synaptic connections, [883] synthesis, [238, 403, 842, 987, 667] system identification, [1177, 1552] sytem identification, [1175] taining, [1377] taxonomy, [970] teaching, [1085] time series, [822, 1164, 1765, 1846, 741, 780] time series prediction, [486, 770] topology, [79, 323, 223, 845, 961, 986, 1047, 1048, 1083, 1107, 1186, 1241, 1263, 1276, 1321, 1356, 1382, 1384, 1393, 1477, 1502, 1529, 1557, 1723, 1843, 601] topology design, [875, 1085] trading, [1445] Subject index 53 training, [177, 199, 295, 361, 362, 813, 201, 363, 389, 428, 832, 844, 859, 866, 868, 877, 896, 917, 922, 924, 972, 980, 989, 993, 998, 1017, 1025, 1044, 1053, 1066, 1068, 1096, 1109, 1123, 1124, 1138, 1148, 1149, 1203, 1208, 1214, 1232, 1254, 1284, 1295, 1304, 1312, 1315, 1349, 1375, 1380, 1398, 1417, 1433, 1470, 1485, 1499, 1503, 1517, 1538, 1542, 1549, 1552, 1555, 1576, 1586, 1625, 1646, 1654, 1679, 1705, 1718, 1724, 1784, 1807, 489, 546, 554, 560, 575, 622, 631, 656, 705, 721, 724, 735, 745, 778] [1788] [101] traning, [1608] tuning, [1100] [174, 408, vetting, [1122] visualisation, [607] [1804] novelty filter, pattern recocognition, [328] [1174] NP-complete problems, [434] allocation, adaptive, pattern recognition [758] neural network, [1832] optics lasers, [1669, 752, 756] photometry, [997] [696] optimization, [284, 354, [507] constrained, [1009] wavelet, [639] cutting problem, [891] wavelets, [702] expert systems, [1108] weight optimization, [293] global, [855, 1254] weights, Pareto, [1727] neural networks 7evolution, [662] neural networks 7fuzzy, [617] neural networks?, massively, NeuroGraph, sleep, niche, NMR gas sensor, [489] hand writing, [1826] hand written, [1375] hand-written characters, handwriting, [1820] [1243, 1246] handwritten Chinese characters, [1606] spectrum, [654] speech, [539, 610] time-series, [700] traffic sign, [1293] pattern search, [881] [810] PCA, [793] [1012] PCR-microchip, [807] parallel processing, [44] parameter estimation, [882, 1650] peanuts aflatoxin, [197] parsing, [426] particle swarm, [787] [63] [1358, 1596, [812, 192, 238, 403, 818, 821, 916, 1045, 1271, 1579, 1681, 1803, 522, 620] [385, 1480] [496] pedagogy student success, parameters path planning, [1513, 657, [261] [479, 480] [1281] [1832] [1721] [1495, 1561] patent, color, paper currency, [21] 495] [564] [1041] neurology motoneurons, coin, [1820, 547] parallel GP, optimization, [1285, 1766] neural networks, [888] neural stimulation classification, [1561] parallel GA neural networs Chinese characters, [1814] natural language, [466, 285, 12, 99, 350, 362, 436, 440, 197, 363, 378, 479, 480, 829, 855, 858, 979, 1054, 1110, 1202, 1273, 1317, 1411, 1491, 1538, 1685, 1687] FPGA, [1810] [47] parallel GA, [1292, 1533, neural networks/independent component analysis, [563] waveform, parallel, [1444] 1764, 1803] knowledge-based, classifiers, character, machine learning, optimizing neural networks 7control, [1728, 1853] neural networks 7learning, 429, 274, 450, 35] transport networks, [481] [771] [1681] 808] walking, XOR-problem, bill, face, optimisation [1804] [78] [137, 111, 194, 304, 402, 271, 813, 211, 212, 818, 908, 955, 969, 1136, 1244, 1350, 1431, 1447, 1525, 1582, 1710, 1757, 499, 524, 526, 540, 558, 573, 626, 636, 755] [1067] operators VLSI, xor problem, pattern recognition, operating systems multi-objective, [197, 855, 905, 955, 1132, 1298, 621] [1636] patterb recognition, 1143, 1170] vector quantization, [1169] obstacle avoidance, non-supervised learning, [1056] optical computing training data, tutorial, imaging, PEPNet, [622] [1491] perceptrons, [443, 405, 413, 540] fuzzy, [1312] topology, [1588] performance, [46] permutations, [227] 54 Genetic algorithms and neural networks pharmacology, [1601, 1697] pharmasy, [544] physics atomic, [1076, 1885] high energy, [1632] high-energy, [531] melting points, [1834] molecular, [1783, 1816, 1868, 608, 711] [672] photonics, [1586] plasma, [894] quantum, [611] radiation, [1857] solid state, [894] physiology, [791] [1626] saccade, [1354] PID controllers, [1509] planning, [1862] pollution [591] monitoring, [1883] polymerisation, [1866] [1690] popular neural networks, [768] problem solving glycerol, [768] cooperative, [1538] 200, [1593, 525] 30, [361] 40, [363] 50, [1435] infinite, [24, 27] potentials process bio-, [1601, 1689] protection protein folding, model parameters, [60] neural networks, [591] nonlinear, [1167] symbolic, [1836] fault diagnosis, [1524, 1825] binding sites, [806] de novo, [931, 946] lattice model, [1593] prediction, [1521] biosphere, [789] [852] classification, [797] forest, [781] [795] proteins, apolipoprotein epsilon4, [605] REM, [100] remote sensing, [1031, 1086, 1314, 1417, 1687, 1712] NMR, [1831] image analysis, QSAR, [1391] image segmentation, [783] secondary structure, [1054, 1521] moisture, [1753] structure, ocean, [685] [999, 1084] dementia, [605] [20] [58] designing neural networks, [1068] [26] GA and neural networks, QSAR, [1261, 1275, QSPR, [1741] review data mining, psychology physiological, retation control, psychiatry [1593] quadratic programming, [1311] quality [399, 473, 482, 483, 1149] in engineering, [36] machine learning, [815] neural Darwinism, [277] neural networks, [814, 1087, 1151] sake, [1416] neural networks and evolutionary computing, [1150] quality control, [1259, 534] quantum computer, [56, 505, 57] neural networks in materials science, [1116] neural network, [1185] neuro-fuzzy rule generation, [549] neural networks, [800] soft computing, [1051] SOM, [1761] quantum computing neural networks, [1050, 1405] [648] radar, prediction [976, 1881] reliability [437] [1885] power nuclear, regression, [14] 1320, 1330, 743, 754] 10, red wine adulteration, QAP, [1443] [654] probabilistic reasoning, [1442] population size interatomic, [1617] structure prediction, [527] control, polymers, prisoner’s dilemma, plastics, [674] generator windings, [1715, 1740] particle, x-ray, stock markets, [109, 1568, training neural networks, [1068] RNA 526] folding, electric load, [1094] Raman spectroscopy, [654] melting points, [1834] reasoning, [995] neural networks, [1696] recycling [1081] robot autonomous, 45] [1104, 1228, Subject index 55 biped, [1578] processors, control, [1104, 1228] satellite communication, mobile, [879, 1140, filters, [668] impulse response, [1570] [1788] medical, [1603] [1225] monitoring, [1430] [1519] neural network-based, disruptive, [41] neural networks, great pressure, [758] source separation, [640] sexual, [1654] speech, [640, 750] self-organizing map, [1421] vector quantisation, [1506] semiconductors, [1339] wavelets, segmentation, [835] [1292] 1296, 762] texture, robot control, [357] selection, robotics, [142, 99, 243, 244, 245, 313, 206, 246, 246, 247, 248, 249, 250, 251, 252, 253, 254, 930, 1548] robotics autonomous, [256, 257, [1497, 675, 677, 710] [1494] touch, [1369] intelligent, [1128] sensitization, [214] manipulators, [1609] sensor [1003, 1480, 1558, 1578, 45, 48, 508, 525, 569, 623, 748, 1861, 765] path planning, [1318] planning, [987] sensoring, [989] walking, [1799] robots autonomous, [401, 1023] walking, [1512] roofs, [1237] rough sets, [1197] routing location, 1747, 540] [590] fluid velocity, [721] traffic, [196] gas, [688, 1873] smell, [1217] sensors electronic nose, [1584] gas, [489, 596] placement, [1262] soft sensors, [713] [537] [1664, 599] [1662, 1673, [1272, 1751] [1051] [804] software reliability, [1419] software testing, [1191] solar energy, [794] SOM, [1421, 616] fuzzy, [1272] learning, [742] [1804] spacecraft solar sail, forming, [701] springback, [788] welding, [784] [1333] signal procesing [1229] medical, sales forecasting, [621] SANE, [944, 1127] [285, 117, NIR, [776] spectra radiation, [1830] signal processing, [97, 284, 365, 937, 1014, 1029, 1099, 1169, 1447, 1638, 1786] signal processing blind source separation, [655] spactroscopy 130, 1033, 1471] [739] spectrometry, [1857] [107] spectroscopy FT-IR, [768] NIR, [499, 799] NMR, [1831, 730] Raman, [654] [904] classification, [810] ECG, [1516, 810] speech recognition, [82] feature selection, [1435, 1788] speech synthesis, [631] [1211, 1411, 1453] load, popular, soft sensors 7design, sheet metal rule-based systems JSS, soft computing sonar, 1699, 1768] job shop, [40] locomotion, b-spline, scheduling, discrete, [1015] [537] 1581, 1677, 1827, 549] [439, 117, 22, data fusion, airfoil, [1064, 1418, [426, 1211, [265, 932, [38] fuzzy, [711] 872] sensoring, vehicle, rules, silicon clusters, simulation, [989] shape design, fuzzy, [640] 1453] [655] rule based systems, signal processing/BSS, simulated annealing, satellite, fuzzy, [1118, 1631, 1765, 1846, 1856, 1858, 526, 641] senses hydraulic, mobile, [1106, 1134, 1141, 1309] 503, 525, 734] control, [997] [498] 56 Genetic algorithms and neural networks static security, [1343] air pollution, [747, 761] control, statistical models, [1787] economic, [1440] evolutionary optimization, forecasting, statistics [1164, 1439, fuzzy controllers, [1564] [30] [34] 576, 763, 780] higher order, time series, fuzzy systems, [640] Mackey-Glass, [1569] non-linear, [741] [1167] steel prediction, corrosion, [1670] stainless, [1670] stock market, [1282, 1763, 1765, 1774, 1839, 1845, 1846, 560, 770] [674] sun spots, [486] sunspots, [1212] [320, 321] strain testing, [1421] timeseries prediction, [1186] [532] [1552] teaching, [1005] telecommunication, [939] [1072] telecommunications ATM, [1458, 1705, [733] steering, tomography, [820] vehicle routing, trading, [31] vehicles [53] traffic prediction, [726] sign recognition, [1153] transformers, 1759] [1524, 618, 687] bandwidth allocation, [1643] fault diagnosis, [1531] iron loss, [1850] CCS, [706] network design, [706] transient stability, neural networks, [1527] transmission lines routing, [665] protection, test cases [1802] [1539] [354] testing liver, [974] materials, [566] text book driver assistance, [1777] [1680] [37, 1336] autonomous, [1686] navigation, [1686] underwater, [762] vibrations, [1015] vision early, VLSI, [645] [153] design, FPGA, [1804, 557] [501, 535, 571] [764] [587] [515, 283, [929] walking control, transportation networks, [481] TSP, [235, 1169] standard-cell placement, transportation analog circuits, [664] vehicle VLSI design, transplantation Rosenbrock’s function, neural networks, storage, intraday, [1326, 1499, 1653] [796] system identification, buffers, unit commitment, disease diagnosis, [19] [859, 994, 1018, 1196, 1328, 1570, 1771, 755] [493] vector quantization, survey neural networks, UK, [174] variable selection tomato data mining, [295, 1442, 1564, 1567, 1574] [736] superconductors cooling, [1811] neural networks, short, [53] time-series, in neural networks, neuro-fuzzy systems, [737] stock markets, stock markets trading, [1442, 1564, 1567] [1558] water distribution systems, [1793] water loss tomato, [733] 286, 12, 1161] neural networks, water resources, [1022] [1657, 1727] turbine wavelets, textbook neural networks, time series, 936, 1447, 1787] gas, [1634] steam, [1634] [1118, 1631, 603] [862] www [882, 911, tutorial, [778] usage, [683] Annual index 4.8 57 Annual index The following table gives references to the contributions by the year of publishing. 1987, [96, 163, 164, 283, 426, 454] 1988, [74, 75, 128, 129, 230, 287, 303, 461, 462] 1989, [76, 82, 90, 118, 127, 132, 133, 137, 213, 231, 232, 328, 364, 421, 433, 463, 464, 465, 466, 467, 468] 1990, 140, 183, 272, 384, 437, [77, 78, 83, 87, 92, 111, 114, 122, 138, 141, 142, 143, 144, 161, 165, 170, 179, 180, 181, 182, 184, 185, 186, 194, 222, 224, 233, 260, 261, 266, 268, 285, 286, 289, 290, 291, 304, 317, 322, 342, 377, 12, 385, 390, 393, 402, 409, 410, 414, 415, 419, 422, 434, 438, 443, 455, 469, 470] 139, 189, 297, 386, 472, 145, 146, 195, 214, 298, 308, 394, 397, 476, 812] 1991, 147, 215, 311, 398, [85, 95, 97, 99, 105, 107, 120, 121, 148, 149, 159, 162, 167, 175, 187, 234, 235, 239, 262, 264, 267, 277, 320, 324, 350, 367, 368, 369, 372, 423, 425, 427, 435, 442, 451, 458, [68, 69, 70, 79, 80, 81, 88, 91, 93, 98, 102, 104, 11, 112, 113, 115, 119, 125, 126, 131, 134, 150, 151, 169, 171, 172, 173, 174, 177, 190, 191, 192, 198, 199, 202, 216, 217, 218, 220, 221, 225, 226, 227, 228, 229, 236, 237, 238, 240, 241, 242, 243, 244, 245, 263, 270, 271, 273, 279, 280, 284, 288, 293, 294, 295, 296, 301, 302, 306, 307, 313, 316, 321, 323, 325, 326, 329, 330, 331, 332, 337, 338, 343, 344, 345, 346, 354, 355, 361, 362, 366, 380, 387, 391, 392, 399, 401, 408, 412, 417, 420, 429, 432, 436, 439, 440, 457, 473, 474, 481, 482, 813, 814, 815, 816] 1993, 103, 153, 196, 210, 253, 281, 319, 351, 373, 400, 430, 453, 819, [71, 72, 73, 84, 86, 89, 94, 100, 106, 108, 109, 110, 116, 117, 123, 124, 130, 135, 154, 155, 156, 157, 158, 160, 166, 168, 176, 178, 197, 200, 201, 1862, 203, 204, 205, 206, 207, 208, 211, 212, 219, 223, 246, 247, 248, 249, 250, 251, 254, 255, 256, 257, 258, 259, 265, 269, 274, 275, 282, 292, 299, 300, 305, 309, 310, 312, 314, 315, 327, 333, 334, 335, 336, 339, 340, 341, 347, 348, 352, 353, 356, 357, 358, 359, 360, 363, 365, 370, 374, 376, 378, 379, 381, 382, 383, 388, 389, 395, 403, 404, 405, 406, 407, 411, 413, 416, 418, 424, 431, 441, 444, 445, 446, 447, 13, 448, 449, 450, 456, 459, 460, 475, 477, 478, 479, 480, 483, 817, 820, 821] 101, 152, 193, 209, 252, 276, 318, 349, 371, 396, 428, 452, 818, 828, 840, 852, 864, 876, 888, 899, 911, 922, 933, 941, 953, [822, 823, 824, 22, 825, 826, 23, 829, 830, 831, 832, 833, 834, 835, 836, 837, 838, 841, 842, 843, 844, 845, 846, 847, 848, 849, 850, 853, 854, 855, 856, 857, 858, 859, 860, 861, 862, 865, 866, 867, 868, 869, 870, 871, 872, 873, 874, 877, 878, 879, 880, 881, 882, 883, 884, 885, 886, 889, 890, 891, 892, 24, 893, 894, 895, 896, 897, 900, 901, 902, 903, 904, 905, 906, 907, 908, 909, 912, 25, 913, 914, 915, 916, 917, 918, 919, 920, 923, 924, 925, 926, 927, 1874, 928, 929, 930, 931, 934, 1875, 935, 936, 937, 26, 27, 938, 939, 1876, 942, 943, 944, 945, 946, 947, 948, 949, 950, 951, 954, 28, 29, 955, 30, 956, 957, 958, 959, 960] 827, 839, 851, 863, 875, 887, 898, 910, 921, 932, 940, 952, 1994, 1995, [961, 962, 963, 964, 965, 966, 967, 968, 969, 970, 971, 972, 973, 974, 975, 976, 977, 978, 979, 980, 981, 982, 983, 984, 985, 986, 987, 988, 989, 990, 991, 992, 993, 994, 995, 996, 997, 998, 999, 1000, 1001, 1002, 1003, 1004, 1005, 1006, 1007, 1008, 1009, 1010, 1877, 1011, 1012, 1013, 1014, 1015, 1016, 1017, 1018, 1019, 1020, 1021, 1022, 1023, 1024, 1025, 1026, 1027, 1028, 1029, 1030, 31, 1031, 1032, 1033, 1034, 1035, 1036, 1037, 1038, 1039, 1040, 1041, 1042, 1043, 1044, 1045, 1046, 1047, 1048, 1049, 1050, 1051, 1052, 1053, 1054, 1055, 1056, 1057, 1058, 1059, 1060, 1061, 1062, 1063, 1064, 1065, 1066, 1067, 1068, 1069, 1070, 1071, 1072, 1073, 1074, 1075, 1076, 1077, 1078, 1079, 1080, 1081, 1082, 1083, 1084, 1085, 1086, 61, 1087, 1088, 1089, 1090, 1092, 1093, 1094, 1095, 1096, 32, 1097, 1098, 1101, 1102, 1103, 1104, 1105, 1106, 1107, 1108, 1878, 1111, 1112, 1113, 1114, 1879, 1115, 1116, 1119, 1120, 1121, 1122, 1123, 1124, 1125, 1126, 1129, 1130, 1131, 1132, 1133, 1134, 1135, 1136, 1139, 1140, 1141, 1142, 1143, 1144, 1145, 1146, 1149, 1150, 1151, 1860] 1099, 1109, 1117, 1127, 1137, 1147, 1158, 1168, 1178, 1188, 1198, 1208, 1218, 1227, 1237, 1246, 1256, 1265, 1275, 1285, 1294, 1304, 1314, 1322, 1332, 1342, [1152, 1153, 1154, 1155, 1156, 1159, 1160, 1161, 1162, 1163, 1164, 1165, 1166, 1169, 1170, 1171, 1172, 1173, 1174, 1175, 1176, 1179, 1180, 1181, 1182, 1183, 1184, 1185, 1186, 1189, 1190, 1191, 1192, 1193, 1194, 1195, 1196, 1199, 1200, 1201, 1202, 1203, 1204, 1205, 1206, 1209, 1210, 33, 1212, 1213, 1214, 1215, 1216, 1219, 1220, 1221, 1222, 1223, 62, 1224, 1225, 1228, 1229, 1230, 1231, 1232, 1233, 1234, 1235, 34, 1238, 1239, 1240, 1241, 1242, 1243, 1244, 1247, 1248, 1249, 1250, 1251, 1252, 1253, 1254, 1257, 1258, 1259, 1260, 1261, 1262, 35, 1263, 1266, 1267, 1268, 1269, 1270, 1271, 1272, 1273, 1276, 1277, 1278, 1279, 1280, 1281, 1282, 1283, 1286, 1287, 1288, 1289, 1290, 36, 1291, 1292, 1295, 1296, 1297, 1298, 1299, 1300, 1301, 1302, 1305, 1306, 1307, 1308, 1309, 1310, 1311, 1312, 1315, 1316, 37, 1317, 1318, 1880, 1319, 1320, 1323, 1324, 1325, 1326, 1327, 1328, 1329, 1330, 1333, 1334, 1335, 1336, 1337, 1338, 1339, 1340, 1343, 1344, 1345, 38] 1157, 1167, 1177, 1187, 1197, 1207, 1217, 1226, 1236, 1245, 1255, 1264, 1274, 1284, 1293, 1303, 1313, 1321, 1331, 1341, 1351, 1361, 1371, 1381, 1391, 1401, 1411, 1421, 1430, 1439, 1449, 1459, 1469, 1479, 1487, 1496, 1506, 1515, 1524, 1533, 1543, 1552, 1562, 1572, [1211, 1346, 1347, 1348, 1349, 1350, 1352, 1353, 1354, 1355, 1356, 1357, 1358, 1359, 1360, 1362, 1363, 1364, 1365, 1366, 1367, 1368, 1369, 1370, 1372, 1373, 1374, 1375, 1376, 1377, 1378, 1379, 1380, 1382, 1383, 1384, 1385, 1386, 1387, 1388, 1389, 1390, 1392, 1393, 1394, 1395, 1396, 1397, 1398, 1399, 1400, 1402, 1403, 1404, 1405, 1406, 1407, 1408, 1409, 1410, 1412, 1413, 1414, 1415, 1416, 1417, 1418, 1419, 1420, 1422, 1423, 1424, 1425, 1426, 1427, 1428, 1429, 1881, 1431, 1432, 1433, 1434, 1435, 1882, 1436, 1437, 1438, 1440, 1441, 1442, 1443, 1444, 1445, 1446, 1447, 1448, 1450, 1451, 1452, 1453, 1454, 1455, 1456, 1457, 1458, 1460, 1461, 1462, 1463, 1464, 1465, 1466, 1467, 1468, 1470, 1471, 1472, 1473, 1474, 1475, 1476, 1477, 1478, 1480, 1481, 1482, 1483, 1883, 1484, 39, 1485, 1486, 1488, 1489, 1490, 1491, 40, 1492, 1493, 1494, 1495, 1497, 1498, 1499, 1500, 1501, 1502, 1503, 1504, 1505, 1507, 1508, 1509, 1510, 1511, 1512, 41, 1513, 1514, 1516, 1517, 1518, 1519, 1520, 1521, 1522, 1884, 1523, 1525, 1526, 1527, 1528, 1529, 1530, 1531, 1532, 42, 1534, 1535, 1536, 1537, 1538, 1539, 1540, 1541, 1542, 1544, 1545, 43, 1546, 1547, 1548, 1549, 1550, 1551, 1553, 1554, 1555, 1556, 1557, 1558, 1559, 1560, 1561, 1563, 1564, 1565, 1566, 1567, 1568, 1569, 1570, 1571, 1573, 1574, 1575, 1576, 1577, 1578, 1579, 1580, 1581] 1588, 1597, 1607, 1616, 1626, 1636, 1646, 1656, 1666, 1674, 1682, 1692, 1701, 1710, 1720, 1729, [1582, 1583, 1584, 1585, 1586, 1587, 1589, 1590, 1591, 1592, 1593, 1594, 1595, 1596, 44, 1598, 1599, 1600, 1601, 1602, 1603, 1604, 1605, 1606, 1608, 1609, 1610, 1611, 1612, 1613, 45, 1614, 1615, 1617, 1618, 1619, 1620, 1621, 1622, 1623, 1624, 1625, 1627, 1628, 1629, 1630, 1631, 1632, 1633, 1634, 1635, 1637, 1638, 1639, 1640, 1641, 1642, 1643, 1644, 1645, 1647, 1648, 1649, 1650, 1651, 1652, 1653, 1654, 1655, 1657, 1658, 1659, 1660, 1661, 1662, 1663, 1664, 1665, 1667, 1668, 46, 1669, 1670, 1671, 47, 48, 1672, 1673, 49, 1675, 1676, 1677, 1678, 1679, 1680, 1885, 1681, 1683, 1684, 1685, 1686, 1687, 1688, 1689, 1690, 1691, 1693, 1694, 1695, 1696, 63, 1697, 1698, 1699, 1700, 1702, 1703, 1704, 1705, 1706, 1707, 1708, 1709, 50, 1711, 1712, 1713, 1714, 1715, 1716, 1717, 1718, 1719, 1721, 1722, 1723, 51, 1724, 1725, 1726, 1727, 1728, 1730, 1731, 1732, 1733, 1734, 1735, 1736] 1996, 136, 188, 278, 375, 471, 1992, 1091, 1100, 1110, 1118, 1128, 1138, 1148, 1997, 1998, 58 1999, Genetic algorithms and neural networks [1737, 1738, 1739, 1740, 1741, 1742, 1743, 1744, 1745, 1746, 1747, 1748, 1749, 52, 1750, 1751, 1752, 1753, 53, 1754, 1755, 1756, 1757, 1758, 1759, 1760, 1761, 1762, 1763, 1764, 1765, 1766, 1767, 1768, 1769, 1770, 1771, 1772, 1773, 1774, 1775, 1776, 1777, 1778, 1779, 1780, 1781, 1782, 1783, 1784, 1785, 1786, 1787, 1788, 1789, 1790, 1791, 54, 1792, 1793, 1794, 1795, 1796, 1797, 1798, 64, 1799, 1800, 1801, 1886, 1802, 1803, 1804, 65, 1805, 1806, 1807, 1808, 1809, 1810, 1811, 1812, 1813, 66, 1814, 1815, 1816, 1817, 1818, 1819, 1820, 1821, 1822, 1823, 1824, 1825, 1826, 1827, 1828, 1829, 1830, 1831, 1832, 1833, 1834, 1835, 1836, 1837, 1838, 1839, 1840, 1841, 1842, 1843, 1844, 1845, 55, 1846, 1847, 1848, 1849, 1850, 1851, 1852, 1853, 1854, 1855, 1856, 1857, 1858, 1859] 2002, [484, 485, 486, 487, 488, 489, 490, 493, 56, 494, 495, 496, 497, 498, 499, 500, 501, 504, 505, 14, 506, 507, 508, 509, 510, 511, 512, 515, 516, 517, 1863, 1864, 518, 519, 520, 521, 522, 525, 526, 527, 528, 529, 530, 531, 532, 533, 1865, 536, 537, 538, 539, 1866, 540, 1867, 541, 542, 543, 546, 1868, 547, 548, 549, 550, 551, 552, 553, 554, 557, 558, 559, 560, 561, 562, 563, 564, 1869, 565, 568, 569, 570, 571, 572, 573, 574, 668] 491, 502, 513, 523, 534, 544, 555, 566, [575, 57, 576, 577, 578, 579, 581, 15, 582, 583, 584, 585, 586, 587, 588, 589, 590, 592, 593, 594, 595, 596, 597, 598, 599, 600, 1870, 601, 16, 603, 604, 605, 606, 607, 608, 17, 609, 610, 611, 612, 614, 615, 616, 617, 618, 619, 620, 621, 622, 623, 624, 626, 627, 628, 629, 630, 631, 632, 633, 634, 18, 635, 637, 638, 639, 1871, 640, 641, 642, 643, 644, 645, 646, 648, 649, 650, 651] 580, 591, 602, 613, 625, 636, 647, 2000, 492, 503, 514, 524, 535, 545, 556, 567, 2001, 660, 673, 685, 696, 704, [652, 653, 654, 655, 656, 657, 658, 659, 661, 662, 663, 664, 665, 666, 667, 669, 670, 671, 672, 674, 675, 676, 677, 678, 679, 680, 681, 682, 683, 684, 686, 687, 688, 689, 690, 691, 692, 692, 693, 694, 695, 19, 697, 20, 698, 1872, 699, 700, 701, 702, 703, 1873, 705, 706, 707, 708, 709, 710, 711, 712] 2003, [713, 714, 715, 716, 717, 718, 719, 720, 721, 722, 723, 724, 725, 726, 727, 728, 729, 730, 731, 732, 58, 733, 734, 735, 736, 737, 738, 739] 2004, [740, 741, 742, 743, 744, 745, 746, 747, 748, 749, 750, 751, 752, 753, 754, 755, 756, 1861] 2005, [757, 758, 759, 760, 761, 762, 763, 764, 765, 766, 767, 768, 769] 2006, [770, 771, 772, 773, 774, 775, 776, 777, 778] 2007, [67, 779, 780, 781, 59, 782, 783, 784, 785, 786, 787, 788, 789, 790, 791, 792] 2008, [793, 794, 795, 796, 797, 798] 2009, [799, 800, 801, 802, 803, 804, 805, 806, 807, 808] 2010, [809, 21, 60, 810] 2011, [811] Geographical index 4.9 59 Geographical index The following table gives references to the contributions by country. • Algeria: [809] • Argentina: [1080, 1163, 1174, 741] • Australia: [482, 101, 483, 868, 872, 1005, 1027, 1031, 1032, 1039, 1055, 1115, 1143, 1146, 1147, 1197, 34, 1286, 1311, 1332, 1391, 1413, 1427, 1469, 1491, 1497, 1526, 1535, 1569, 1585, 46, 1697, 1704, 1730, 1768, 1782, 1792, 1807, 521, 649, 701, 734] • Austria: [988, 1002, 1238, 1307, 1503, 1722, 1774, 15, 714] • Azerbaithzan: [1052] • Bangladesh: [808] • Belgium: [137, 138, 140, 141, 142, 143, 144, 139, 145, 147, 148, 149, 150, 151, 436, 941, 1057, 1108, 1252, 1378, 1764, 500, 501, 572, 586, 718, 781] • Bosnia and Herzegovina: [704, 737, 758] • Brazil: [131, 961, 978, 1056, 1079, 1106, 1154, 1352, 1384, 1883, 1611, 1622, 1625, 1645, 1724, 1766, 1780, 1786, 1830, 527, 669, 711, 722, 725, 767, 804] • Bulgaria: [1091, 1452, 1663] • Byelorussia: [1449] • Canada: [550, 820, 826, 880, 924, 1065, 1092, 1161, 1195, 37, 1336, 38, 1346, 1519, 1523, 1525, 1540, 1589, 44, 1701, 1810, 1831, 485, 577, 676, 696, 774] • Chile: [991, 579, 644] • China: [1254, 1218, 873, 1060, 1063, 1087, 1110, 1878, 1118, 1123, 1138, 1166, 1215, 1234, 1284, 1285, 1289, 1291, 1304, 1325, 1333, 1345, 1373, 1374, 1398, 1400, 1420, 1432, 1433, 1445, 1508, 1524, 1528, 1529, 1530, 1531, 42, 1537, 1568, 1669, 1670, 1703, 1706, 1708, 50, 1710, 1713, 1759, 1778, 1794, 1795, 1834, 1837, 1849, 492, 516, 519, 526, 554, 561, 1869, 584, 596, 639, 642, 647, 682, 702, 706, 721, 733, 739, 764, 775, 788, 789, 796, 805, 806, 807, 515, 903, 1048, 1454, 1606, 1653, 52, 1773, 1789, 1814, 559, 624, 640, 707, 709, 732, 735] • Cyprus: [345, 1231] • Denmark: [853, 1096, 1113, 1130, 1140, 1250, 1825, 59] • Egypt: [962, 1386, 1412, 1715, 1740, 1798] • Finland: [504, 277, 346, 223, 347, 882, 925, 972, 1000, 1085, 1860, 1156, 1186, 1212, 1297, 1320, 1392, 1421, 1426, 1444, 1494, 1510, 1594, 1648, 1716, 1717, 1731, 1791, 1843, 1857, 1859, 560, 562, 677, 710, 724, 747, 748, 750, 1861, 757, 761, 780, 791] 1770, 1783, 1800, 65, 1809, 1812, 1844, 1847, 1855, 533, 536, 537, 542, 552, 557, 567, 568, 574, 581, 587, 589, 591, 1870, 604, 606, 619, 629, 645, 650, 651, 652, 655, 698, 708, 717, 730, 744, 759, 800] • Greece: [665, 380, 381, 1459, 1664, 1666, 1686, 1850, 511, 618, 625, 687, 749, 797] • Hungary: [452, 453, 1256, 1772, 799] • Iceland: [1157, 1362, 1779] • India: [372, 431, 839, 929, 950, 955, 1043, 1083, 1183, 1209, 1237, 1277, 1477, 1479, 1489, 1502, 1557, 1584, 47, 1819, 1851, 488, 489, 1868, 549, 660, 689, 19, 20, 728, 67, 779, 803] • Indonesia: [494, 657] • Iran: [743, 754, 784] • Ireland: [802, 168, 772] • Israel: [363, 428, 917, 1350] • Italy: [548, 342, 368, 369, 321, 343, 344, 84, 178, 196, 318, 319, 371, 13, 841, 875, 879, 890, 1054, 1104, 1126, 1152, 1158, 1160, 1165, 1168, 1178, 1213, 1228, 1269, 1369, 1381, 1395, 1521, 1586, 1658, 1685, 1687, 1737, 1749, 1769, 510, 565, 17, 632, 653, 726, 773, 782, 792, 794] • Japan: [703, 272, 442, 202, 273, 288, 296, 355, 100, 152, 153, 154, 155, 156, 157, 158, 1862, 203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 274, 356, 357, 358, 359, 446, 449, 456, 821, 823, 838, 848, 860, 865, 885, 886, 898, 902, 908, 916, 928, 937, 940, 958, 959, 967, 985, 1004, 1877, 1045, 1049, 1062, 61, 1089, 1090, 1094, 1101, 1102, 1124, 1128, 1136, 1142, 1145, 1153, 1179, 1190, 1192, 1194, 1204, 1205, 1225, 1227, 1229, 1235, 1236, 1247, 1248, 1266, 1267, 1268, 1271, 1272, 1287, 1288, 1293, 1300, 1310, 1324, 1335, 1337, 1338, 1342, 1211, 1354, 1359, 1396, 1397, 1399, 1401, 1402, 1404, 1409, 1415, 1416, 1417, 1418, 1424, 1425, 1447, 1450, 1453, 1472, 1476, 1480, 1481, 1488, 1509, 1512, 1513, 1514, 1515, 1532, 1533, 1541, 1546, 1548, 1550, 1551, 1556, 1558, 1563, 1564, 1565, 1570, 1572, 1575, 1577, 1578, 1579, 1581, 1591, 1601, 1608, 1620, 1629, 1637, 1638, 1639, 1649, 1651, 1654, 1660, 1680, 1681, 1683, 1684, 1689, 1691, 1692, 1693, 1694, 1696, 1707, 1711, 1712, 1719, 1721, 1725, 1728, 1732, 1733, 1735, 1775, 1788, 1797, 1799, 1801, 1803, 1804, 1806, 1821, 1822, 1823, 1828, 1832, 1839, 1848, 1853, 517, 520, 522, 530, 538, 555, 563, 564, 570, 573, 588, 611, 630, 762, 765, 766] • Jordan: [1018, 1099] • Kuwait: [785] • Lebanon: [783] • France: [692, 99, 278, 174, 216, 217, 218, 219, 424, 851, 862, 899, 930, 945, 949, 1023, 1177, 1219, 1221, 1303, 1312, 1356, 1365, 1371, 1465, 1466, 1470, 1486, 1604, 1628, 1636, 1665, 1739, 583] • Germany: [222, 260, 261, 105, 262, 350, 80, 104, 11, 263, 307, 316, 387, 457, 103, 106, 197, 314, 315, 351, 352, 378, 388, 477, 478, 479, 480, 818, 827, 829, 831, 852, 856, 863, 867, 881, 909, 912, 919, 920, 921, 933, 935, 1876, 942, 947, 29, 964, 968, 979, 981, 1012, 1019, 1041, 1059, 1068, 1076, 1081, 1114, 1132, 1139, 1180, 1188, 1206, 1217, 1241, 1249, 1264, 1273, 1280, 1283, 1301, 1306, 1321, 1363, 1367, 1372, 1393, 1394, 1410, 1430, 1451, 1467, 1475, 1487, 1505, 1518, 1538, 1587, 1599, 1614, 1634, 1678, 1690, 1695, 1714, 1750, 1761, • Malaysia: [1824, 610, 694] • Mexico: [1765, 1846, 1856, 1858, 486, 668, 770, 771] • New Zealand: [1441, 1468, 1633, 1659, 539, 751] • Norway: [1107] • Poland: [814, 365, 918, 1875, 1029, 1067, 1095, 1129, 1134, 1141, 1263, 1357, 1448, 1455, 1482, 1544, 1553, 1595, 1617, 1623, 1673, 1726, 634, 763] • Portugal: [1164, 1439, 1662, 1864, 609, 755] • Puerto Rico: [1813] 60 Genetic algorithms and neural networks • Romania: [1170, 35, 1422, 1621, 1699, 631] • Russia: [113, 878, 922, 1093, 1270, 1353, 1517, 1542, 1635] • Singapore: [405, 406, 407, 849, 938, 993, 1111, 1474, 1612, 1727, 1818, 524, 534, 1867, 795] • Slovenia: [160, 842, 987, 1078, 1105, 1207, 691] • South Africa: [1616, 740] • South Korea: [305, 934, 1008, 1009, 1044, 1071, 1117, 1159, 1169, 1202, 1224, 1243, 1244, 1245, 1295, 1313, 1316, 1317, 1880, 1319, 1331, 1882, 1492, 1498, 1506, 1603, 1607, 1618, 1619, 1640, 1682, 1688, 1734, 1736, 1757, 1763, 1785, 1820, 1845, 55, 495, 566, 599, 623, 648, 656, 793] 1098, 1246, 1478, 1674, 1836, • Spain: [175, 69, 72, 73, 374, 416, 844, 896, 1021, 1879, 1131, 1167, 1364, 1370, 1383, 1390, 1437, 1438, 1456, 1463, 1554, 1677, 1746, 1808, 497, 509, 558, 575, 578, 597, 598, 600, 635, 646, 679, 745, 778, 790, 801] • Sweden: [379, 1790, 513] • Switzerland: [459, 31, 1274, 1385, 1562, 45, 1652, 1741, 503, 603] • Taiwan: [1863, 858, 1038, 1069, 1072, 1201, 1253, 1318, 1326, 1343, 1368, 1411, 1431, 1458, 1499, 41, 1580, 1600, 1602, 1627, 1631, 1643, 1647, 51, 1751, 1755, 1756, 1758, 1784, 1817, 498, 507, 553, 621, 636, 658, 659, 688, 731, 777, 786] • Thailand: [1461, 1754, 613, 798, 810] • The Czech Republic: [1026, 1144, 1493, 1522, 1560, 1597, 1613, 1841, 671, 1046, 1220, 1258, 1276, 545, 643, 672] • The Netherlands: [107, 367, 102, 229, 309, 828, 854, 911, 977, 995, 1120, 1135, 1182, 1208, 1230, 1406, 1464, 1471, 1507, 1675] • The Slovak Republic: [686, 699, 32, 33, 54, 592] • Tunisia: [760, 769] • Turkey: [887, 986, 1155, 1442, 1516, 1552, 1805, 641, 673, 705] • U Arab Emirates: [869, 1064] • Ukraina: [1013, 1251, 1446, 1679, 1826] • United Kingdom: [114, 215, 239, 324, 386, 394, 244, 245, 337, 338, 361, 250, 251, 252, 253, 254, 339, 340, 341, 395, 400, 926, 927, 931, 932, 939, 161, 397, 399, 255, 834, 946, 179, 398, 108, 256, 835, 963, 194, 240, 246, 257, 843, 965, 266, 241, 247, 269, 850, 966, 393, 242, 248, 300, 871, 983, 214, 243, 249, 310, 914, 989, 990, 994, 999, 1001, 1003, 1011, 1014, 1016, 1035, 1037, 1042, 1050, 1058, 1070, 1084, 1086, 1088, 1097, 1122, 1133, 1162, 1173, 1176, 1198, 1200, 1216, 1222, 1226, 1233, 1240, 1257, 1262, 1265, 1290, 36, 1302, 1305, 1309, 1314, 1323, 1329, 1341, 1344, 1348, 1355, 1366, 1380, 1407, 1423, 1881, 1434, 1443, 1457, 1460, 1462, 40, 1495, 1534, 1539, 1543, 43, 1547, 1559, 1561, 1566, 1571, 1590, 1592, 1624, 1641, 1644, 1650, 1885, 1700, 1702, 1709, 1718, 1723, 1729, 1744, 1745, 53, 1760, 1762, 1771, 1781, 1796, 1816, 1835, 1842, 1852, 1854, 487, 506, 523, 532, 540, 541, 571, 580, 582, 16, 614, 633, 637, 1871, 662, 680, 685, 715, 736, 742, 753] • United States: [230, 287, 303, 461, 462, 90, 132, 133, 213, 231, 232, 328, 433, 463, 464, 465, 466, 467, 468, 78, 92, 111, 165, 180, 181, 182, 183, 184, 185, 186, 233, 268, 286, 289, 290, 291, 304, 402, 409, 410, 414, 419, 434, 438, 443, 469, 470, 85, 146, 167, 187, 188, 189, 195, 234, 235, 297, 375, 435, 471, 472, 476, 91, 93, 112, 134, 173, 177, 190, 191, 192, 198, 199, 220, 221, 236, 237, 238, 271, 293, 294, 295, 302, 306, 330, 331, 332, 401, 408, 412, 420, 429, 439, 440, 473, 474, 481, 813, 815, 816, 89, 94, 117, 124, 130, 135, 166, 176, 193, 200, 201, 258, 259, 292, 299, 333, 334, 335, 336, 348, 389, 403, 411, 445, 460, 475, 817, 819, 824, 22, 825, 832, 833, 836, 837, 840, 845, 846, 847, 855, 859, 861, 864, 870, 874, 876, 877, 883, 884, 888, 889, 891, 892, 893, 894, 895, 897, 900, 901, 905, 906, 907, 913, 915, 923, 1874, 936, 944, 948, 951, 952, 953, 954, 28, 30, 956, 957, 960, 969, 970, 971, 973, 980, 982, 984, 992, 996, 997, 998, 1006, 1007, 1010, 1015, 1020, 1022, 1024, 1025, 1028, 1033, 1034, 1040, 1047, 1053, 1061, 1066, 1073, 1074, 1075, 1077, 1082, 1100, 1109, 1112, 1116, 1119, 1121, 1125, 1127, 1148, 1149, 1150, 1151, 1171, 1172, 1175, 1184, 1187, 1189, 1191, 1196, 1199, 1203, 1210, 1214, 62, 1242, 1255, 1259, 1260, 1261, 1278, 1279, 1281, 1282, 1292, 1294, 1296, 1298, 1299, 1308, 1315, 1322, 1327, 1328, 1330, 1334, 1339, 1340, 1360, 1361, 1376, 1377, 1379, 1387, 1389, 1403, 1405, 1408, 1414, 1419, 1435, 1436, 1440, 1473, 1483, 39, 1490, 1496, 1500, 1884, 1527, 1536, 1545, 1549, 1567, 1574, 1576, 1588, 1593, 1598, 1605, 1610, 1630, 1632, 1642, 1646, 1655, 1656, 1657, 1667, 1668, 1671, 1672, 49, 63, 1705, 1720, 1742, 1743, 1747, 1748, 1752, 1753, 1767, 1776, 1787, 1793, 64, 1886, 1802, 1811, 66, 1815, 1827, 1829, 1833, 1840, 484, 490, 491, 496, 499, 502, 14, 508, 512, 514, 518, 525, 529, 531, 1865, 535, 543, 544, 546, 547, 569, 576, 585, 590, 593, 595, 601, 602, 607, 612, 616, 617, 620, 622, 626, 627, 628, 18, 654, 664, 683, 684, 695, 697, 700, 712, 713, 716, 719, 727, 729, 58, 738, 752, 756, 768, 776, 787, 21, 60] • Unknown country: [812, 822, 976, 1181, 1185, 1239, 1275, 1351, 1358, 1375, 1382, 1388, 1428, 1429, 1484, 1485, 1501, 1504, 1511, 1520, 1555, 1573, 1596, 1626, 1661, 48, 1676, 1698, 1738, 1777, 1838, 56, 505, 551, 556, 57, 594, 605, 608, 615, 638, 661, 666, 667, 670, 674, 675, 681, 690, 693, 1872, 1873, 720, 723, 746] • Venezuela: [396, 1347, 1582] • Yugoslavia: [1030, 1609] Bibliography [1] John H. Holland. Genetic algorithms. Scientific American, 267(1):44–50, 1992. ga:Holland92a. [2] Jarmo T. Alander. An indexed bibliography of genetic algorithms: Years 1957-1993. Art of CAD Ltd., Vaasa (Finland), 1994. (over 3000 GA references). [3] David E. Goldberg, Kelsey Milman, and Christina Tidd. Genetic algorithms: A bibliography. IlliGAL Report 92008, University of Illinois at Urbana-Champaign, 1992. ga:Goldberg92f. [4] N. Saravanan and David B. Fogel. A bibliography of evolutionary computation & applications. Technical Report FAU-ME-93-100, Florida Atlantic University, Department of Mechanical Engineering, 1993. (ftp: //magenta.me.fau.edu/pub/ep-list/bib/EC-ref.ps.Z) ga:Fogel93c. [5] Thomas Bäck. Genetic algorithms, evolutionary programming, and evolutionary strategies bibliographic database entries. (personal communication) ga:Back93bib, 1993. [6] Thomas Bäck, Frank Hoffmeister, and Hans-Paul Schwefel. Applications of evolutionary algorithms. Technical Report SYS-2/92, University of Dortmund, Department of Computer Science, 1992. ga:Schwefel92d. [7] David L. Hull. Uncle Sam wants you. Science, 284(5417):1131–1133, 14. May 1999. [8] Leslie Lamport. LATEX: A Document Preparation System. User’s Guide and Reference manual. AddisonWesley Publishing Company, Reading, MA, 2 edition, 1994. [9] Alfred V. Aho, Brian W. Kernighan, and Peter J. Weinberger. The AWK Programming Language. AddisonWesley Publishing Company, Reading, MA, 1988. [10] Diane Barlow Close, Arnold D. Robbins, Paul H. Rubin, and Richard Stallman. The GAWK Manual. Cambridge, MA, 0.15 edition, April 1993. [11] Stefan Bornholdt and Dirk Graudenz. General asymmetric neural networks and structure design by genetic algorithms. Neural Networks, 5(2):327–334, 1992. ga:Bornholdt92a. [12] Carsten Peterson. Parallel distributed approaches to combinatorial optimization: benchmark studies on traveling salesman problem. Neural Computation, 2:261–269, 1990. ga:Peterson90. [13] Salvatore Arnone, Andrea Loraschi, and Andrea Tettamanzi. A genetic approach to portfolio selection. Neural Network World, 3(6):597–604, 1993. ga:Tettamanzi93a. [14] Eric B. Baum and Igor Durdanovic. Evolution of cooperative problem solving in an artificial economy. Neural Computation, 12(12):2743–2775, December 2000. ga00aEBBaum. [15] Christian Keber and Matthias G. Schuster. Evolutionary computation and the vega risk of American put options. IEEE Transactions on Neural Networks, 12(4):704–715, July 2001. ga01aCKeber. [16] M. A. H. Dempster, Tom W. Payne, Yazann Romahi, and G. W. P. Thompson. Computational learning techniques for intraday FX trading using popular technical indicators. IEEE Transactions on Neural Networks, 12(4):744–754, July 2001. ga01aMAHDempster. [17] Marco Russo. Distributed fuzzy learning using the MULTISOFT machine. IEEE Transactions on Neural Networks, 12(3):475–484, May 2001. ga01aMRusso. [18] Vasant Dhar and Dashin Chou. A comparison of nonlinear methods for predicting earnings surprises and returns. IEEE Transactions on Neural Networks, 12(4):907–921, July 2001. ga01aVDhar. [19] Sushmita Mitra, Sankar K. Pal, and Pabitra Mitra. Data mining in soft computing framework: a survey. IEEE Transactions on Neural Networks, 13(1):3–14, January 2002. ga02aSMitra. [20] Sushmita Mitra, Sankar K. Pal, and Pabitra Mitra. Data mining in soft computing framework: A survey. IEEE Transactions on Neural Networks, 13(1):3–14, January 2002. ga02aSushmitaMitra. 61 62 Genetic algorithms and neural networks [21] Amorn Wongsarnpigoon and Warren M. Grill. Energy-efficient waveform shapes for neural stimulation revealed with a genetic algorithm. Journal of Neural Engineering, 7(046009):1–11, ? 2010. ga10aAWongsarnpigoon ⇒ http://iopscience.iop.org/1741-2552/7/4/046009/. [22] J. Wirt Atmar. Notes on the simulation of evolution. IEEE Transactions on Neural Networks, 5(1):130–148, January 1994. †toc ga94aAtmar. [23] Anoop K. Bhattacharjya and Badrinath Roysam. Joint solution of low-, intermediate-, and high-level vision tasks by evolutionary optimization: Application to computer vision at low SNR. IEEE Transactions on Neural Networks, 5(1):83–95, January 1994. †toc ga94aBhattacharjya. [24] Xiaofeng Qi and Francesco Palmieri. Theoretical analysis of evolutionary algorithms with an infinite population size in continuous space, part I: Basic properties. IEEE Transactions on Neural Networks, 5(1):102–119, January 1994. †toc ga94aQi. [25] Bruce A. Whitehead and Timothy D. Choate. Evolving space-filling curves to distribute radial basis functions over an input space. IEEE Transactions on Neural Networks, 5(1):15–23, January 1994. †toc ga94aWhitehead. [26] Volker Nissen. Solving the quadratic assignment problem with clues from nature. IEEE Transactions on Neural Networks, 5(1):66–72, January 1994. †toc ga94bNissen. [27] Xiaofeng Qi and Francesco Palmieri. Theoretical analysis of evolutionary algorithms with an infinite population size in continuous space, part II: Analysis of the diversification role of the crossover. IEEE Transactions on Neural Networks, 5(1):120–129, January 1994. †toc ga94bQi. [28] David B. Fogel and Lawrence J. Fogel. Evolutionary computation. IEEE Transactions on Neural Networks, 5(1):1–2, January 1994. †toc ga94dFogel. [29] Günter Rudolph. Convergence analysis of canonical genetic algorithm. IEEE Transactions on Neural Networks, 5(1):96–101, January 1994. †toc ga94dRudolph. [30] David B. Fogel. An introduction to simulated evolutionary optimization. IEEE Transactions on Neural Networks, 5(1):3–14, January 1994. †toc ga94eFogel. [31] Olivier V. Pictet, Michel M. Dacorogna, Bastien Chopard, Mouloud Oussaidene, Roberto Schirru, and Marco Tomassini. Using genetic algorithms for robust optimization in financial applications. Neural Network World, ?(?):?, ? 1995. (to appear) ga95aPictet. [32] M. Lehotsky, V. Olej, and J. Chmumy. Pattern recognition based on the fuzzy neural networks and their learning by modified genetic algorithms. Neural Network World, 5(1):91–97, 1995. †EI M199150/95 ga95bLehotsky. [33] Vladimı́r Kvasnička, Martin Pelikán, and Jiřı́ Pospı́chal. Hill climbing with learning (an abstraction of genetic algorithm). Neural Netw. World (Czech Republic), 6(5):773–796, 1996. †CCA44395/97 ga96aKvasnicka. [34] Leonid Reznik. Controller design: the combination of techniques. Neural Network World, 6(4):691–699, ? 1996. * EI M109110/96 ga96aReznik. [35] L. State, S. Rubin, and R. State. Evolutionary/genetic programming in restricted domains. Neural Parallel Sci. Comput. (USA), 4(4):419–443, 1996. †CCA26497/97 ga96aState. [36] A. M. S. Zalzala and Peter J. Fleming. Genetic algorithms: principles and applications in engineering systems. Neural Netw. World (Czech Republic), 6(5):803–820, 1996. †CCA522817/97 ga96aZalzala. [37] Jean-Yves Potvin, C. Duhamel, and François Guertin. A genetic algorithm for vehicle routing with backhauling. Appl. Intell. Int. J.Artif. Intell. Neural Netw. Complex Probl-Solving Technol (Netherlands), 6(4):345–355, 1996. †CCA10419/97 ga96bJ-YPotvin. [38] Jean-Yves Potvin, C. Duhamel, and François Guertin. A genetic algorithm for vehicle routing with backhauling. Appl. Intell. Int. J.Artif. Intell. Neural Netw. Complex Probl-Solving Technol (Netherlands), 6(4):345–355, 1996. †CCA10419/97 ga96gJ-YPotvin. [39] Phillip D. Stroud. Learning and adaptation in an airborne laser fire controller. IEEE Transactions on Neural Networks, 8(5):1078–1089, September 1997. ga97aPDStroud. [40] R. J. Paul and T. S. Chanev. Optimising a complex discrete event simulation model using a genetic algorithm. Neural Computing & Applications, 6(4):229–237, 1997. †CCA57317/98 ga97aRJPaul. [41] Ting Kuo and Shu-Yuen Hwang. Using disruptive selection to maintain diversity in genetic algorithms. Appl. Intell., Int. J. Artif. Intell. Neural Netw. Complex Probl.-Solving Technol (Netherlands), 7(3):257– 267, 1997. †CCA78594/97 ga97aTingKuo. Bibliography 63 [42] Yee Leung, Yong Gao, and Zong-Ben Xu. Degree of population diversity – a perspective on premature convergence in genetic algorithms and its Markov chain analysis. IEEE Transactions on Neural Networks, 8(5):1165–1176, September 1997. ga97aYeeLeung. [43] Dimitris C. Dracopoulos and S. Kent. Genetic programming for prediction and control. Neural Computing & Applications, 6(4):214–228, 1997. †CCA54949/98 ga97bDCDracopoulos. [44] B. J. Ross. The evolution of concurrent programs. Appl. Intell., Int. J. Artif. Intell. Neural Netw. Complex Probl.-Solving Technol. (Netherlands), 8(1):21–32, 1998. †CCA45891/98 ga98aBJRoss. [45] Dario Floreano and Francesco Mondada. Evolutionary neurocontrollers for autonomous mobile robots. Neural Networks, 11(7-8):1461–1478, October/November 1998. ga98aFloreano. [46] John R. Podlena and Tim Hendtlass. An accelerated genetic algorithm. Int. J. Artif. Intell. Neural Netw. Complex Probl.-Solving Technol. (Netherlands), 8(2):103–111, 1998. †CCA66134/98 ga98aPodlena. [47] Rajeev Kumar and Peter Rockett. Multiobjective genetic algorithm partitioning for hierarchical learning of high-dimensional pattern spaces: a learning-follows-decomposition strategy. IEEE Transactions on Neural Networks, 9(5):822–830, September 1998. ga98aRKumar. [48] Robert A. Dain. Developing mobile robot wall-following algorithms using genetic programming. Appl. Intell., Int. J. Artif. Intell. Neural Netw. Complex Probl.-Solving Technol. (Netherlands), 8(1):33–41, 1998. †CCA45339/98 ga98aRobeDain. [49] S. Baluja and Dan Simon. Evolution-based methods for selecting point data for object localization: applications to computer-assisted surgery. Int. J. Artif. Intell. Neural Netw. Complex Probl.-Solving Technol. (Netherlands), 8(1):7–19, 1998. †CCA49259/98 ga98aSBaluja. [50] Yong Gao, Xiaofeng Qi, and F. Palmieri. Comments on “theoretical analysis of evolutionary algorithms with an infinite population size in continuous space. I. basic properties of selection and mutation” [and reply]. IEEE Trans. Neural Netw. (USA), 9(2):341–343, 1998. †CCA34044/98 ga98aYongGao. [51] Jong-Chen Chen. Problem solving with a perpetual evolutionary learning architecture. Appl. Intell., Int. J. Atif. Intell. Neural Netw. Complex Probl.-Solving Technol. (Netherlands), 8(1):53–71, 1998. †CCA43109/98 ga98bJongChen. [52] B. Porter and C. Allaoui. Evolutionary robustification of digital trajectory-tracking controllers for robotic manipulators. Neural Parallel Sci. Comput, 7(2):277–300, 1999. †CCA79956/99 ga99aBPorter. [53] C. Dunis, A. Harris, Swee Leong, and P. Nacaskul. Optimising intraday trading models with genetic algorithms. Neural Netw. World (Czech Republic), 9(3):193–223, 1999. †CCA92173/ 99 ga99aCDunis. [54] V. Kvasnicka and J. Pospichal. GA simulation of evolution of cognitive artifacts. Neural Netw. World (Czech Republic), 9(1-2):25–42, 1999. †CCA86488/99 ga99aKvasnicka. [55] Doo-Hyun Choi, Se-Young Oh, and Hyeon-Joong Cho. A new fast evolutionary programming algorithm for continuous function optimization. Neural Parallel Sci. Comput. (USA), 7(1):67–75, 1999. †CCA94327/99 ga99bDoo-Choi. [56] Benoit. Biologically plausible learning rules for neural networks and quantum computing. Neurocomputing, 32-33(?):921–926, June 2000. †www /Elsevier ga00aBenoit. [57] Armando Freitas da Rocha, Alfredo Pereira, Jr, and Francisco Antonio Bezerra Coutinho. N-methyl-Daspartate channel and conciousness: from signal coincidence detection to quantum computing. Progress in Neurobiology, 64(6):555–573, August 2001. †www /Elsevier ga01aAFdaRocha. [58] Tor D. Wager and Thomas E. Nicholis. Optimization of experimental design in fMRI: a general framework using a genetic algorithm. NeuroImage, 18(?):293–309, ? 2003. ga03aTDWager. [59] Leena N. Patel, Alan Murray, and John Hallam. Super-lamprey and wave energy: Optimised control of artificially-evolved, simulated swimming lamprey. Neurocomputing, 70(?):1139–1154, ? 2007. ga07aLeenaNPatel ⇒ . [60] O. Akman and J. W. Hallam. Natural selection at work: an accelerated evolutionary computing approach to predictive model selection. Frontiers in Neuroscience, 4(33):–, 8. July 2010. ga10aOAkman ⇒ http: //www.ncbi.nlm.nih.gov/pubmed/20661297. [61] K. Hirota, T. Tsurumaru, A. Motegi, N. Yubazaki, M. Ohtani, and T. Miyajima. A successive learning neuro GA control system shooting an irregular moving object. Neurocomputing (Netherlands), 29(1):27–38, 1995. †EEA89658/95 ga95bHirota. [62] D. McNay, Eric Michielssen, R. L. Rogers, F. A. Taylor, M. Akhtari, and W. W. Sutherling. Multiple source localization using genetic algorithms. Journal of Neuroscience Techniques, 64(?):163–172, February 1996. †Johnson/bib [1888] ga96aMcNay. 64 Genetic algorithms and neural networks [63] V. Booth. A genetic algorithm study on the influence of dendritic plateau potentials on bistable spiking in motoneurons. Neurocomputing (Netherlands), 26-27:69–78, 1998. †CCA68502/99 ga98aVBooth. [64] M. C. Vanier and J. M. Bower. A comparative survey of automated parameter-search methods for compartmental. J. Comput. Neurosci., 7(2):149–171, September-October 1999. * PubMed10515252 ga99aMCVanier. [65] M. Scherg, T. Bast, and P. Berg. Multiple source analysis of interictal spikes: goals, requirements, and clinical value. J. Clin. Neurophysiol, 16(3):214–224, May 1999. * PubMed10426405 ga99aMScherg. [66] R. P. Velthuizen, L. O. Hall, and L. P. Clarke. Feature extraction for MRI segmentation. J. Neuroimaging, 9(2):85–90, April 1999. * PubMed10208105 ga99aRPVelthuizen. [67] Latha Parthiban and R. Subramanian. Intelligent heart disease prediction system using CANFIS and genetic algorithm. International Journal of Biological and Life Sciences, 3(3):157–160, ? 2007. 07aLathaParthiban ⇒ http://www.waset.org/journals/ijbls/v3/v3-3-22.pdf. [68] G. Distefano, M. Capozza, and N. Accornero. Neural networks trained by a genetic algorithm for visualfield diagnosis. In J. P. Morucci, R. Plonsey, J. L. Coatriex, and S. Laxminarayan, editors, Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, volume 14, pages 1028–1029, Paris, France, 29. October - 1. November 1992. IEEE, New York. †P57332 ga:Accornero92a. [69] Enrique A. Alba Torres and José Francisco Aldana Montes. Los algorithmos genéticos como heurı́stico en problemas de optimización. Teaching Technical Report (Monographic) LCC-ID-92/3, Universidad de Málaga, Departemento de Lenguajes y Ciencias de la Computación, 1992. (in Spanish) †Alba Torres ga:Alba92a. [70] Enrique A. Alba Torres, José Francisco Aldana Montes, and José M. Troya. Genetic algorithms as heuristics for optimizing ANN design. Research Technical Report (Monographic) LCC-ID-92/4, Universidad de Málaga, Departemento de Lenguajes y Ciencias de la Computación, 1992. † ga:Alba92b. [71] Enrique A. Alba Torres, José Francisco Aldana Montes, and José M. Troya. Genetic algorithms as heuristics for optimizing ANN design. In Albrecht et al. [1889], pages 683–690. ga:Alba93a. [72] Enrique A. Alba Torres. Aplicación de los algorithmos genéticos para el diseño de redes neuronales [Application of genetic algorithms for the design of neural networks]. Informática y Automática (Spain), 26(2):22–35, June 1993. (in Spanish) * CCA 63954/93 ga:Alba93b. [73] Enrique A. Alba Torres, José Francisco Aldana Montes, and José M. Troya. Full automatic ANN design: a genetic approach. In J. Mira, J. Cabestany, and A. Prieto, editors, Proceedings of the International Workshop on Artificial Neural Networks (IWANN’93), pages 399–404, Sitges (Spain), 9.-11. June 1993. Springer-Verlag, Berlin. * CCA 20428/93 ga:Alba93c. [74] Eric Mjolsness, David H. Sharp, and Bradley K. Alpert. Scaling, machine learning, and genetic neural nets. Technical Report YALEU/DCS/TR-613, 1988. † ga:Alpert88a. [75] Eric Mjolsness, David H. Sharp, and Bradley K. Alpert. Scaling, machine learning, and genetic neural nets. Technical Report LA-UR-88-142, 1988. † ga:Alpert88b. [76] Eric Mjolsness, David H. Sharp, and Bradley K. Alpert. Scaling, machine learning, and genetic neural nets. Advances in Applied Mathematics, 10(2):137–163, December 1989. †ACM/89 ga:Alpert89a. [77] Denis Anthony, Evor L. Hines, John Barham, and David Taylor. The use of genetic algorithms to learn the most appropriate inputs to a neural network. In M. H. Hamza, editor, Artificial Intelligence Application & Neural Networks (AINN’90), pages 223–226, Zürich, 25.-27. June 1990. ACTA Press, Anaheim, CA. ga:Anthony90. [78] Scott Austin. Genetic solutions to XOR problems. AI Expert, 5(12):52–57, December 1990. ga:Austin90b. [79] Alan Scott Austin. Structural level evolution of neural networks. †Back/bib/unp ga:Austin92a. In Fogel and Atmar [1890]. [80] Byoung-Tak Zhang. Learning by genetic neural evolution. Informatik Berichte 93, University of Bonn, 1992. †Muhlenbein93/GA5 ga:B-TZhang92a. [81] N. Baba. Utilization of stochastic automata and genetic algorithms for neural network learning. In Männer and Manderick [1891], pages 431–440. † ga:Baba92a. [82] A. Badii, M. J. Binstead, Antonia J. Jones, T. J. Stonham, and Christine L. Valenzuela. Applications on n-tuple sampling and genetic algorithms to speech recognition. In I. Aleksander, editor, Neural Computing Architectures, pages 172–216. North Oxford Academic, 1989. † ga:Badii89. Bibliography 65 [83] N. R. Ball. Adaptive signal processing via genetic algorithms and self-organizing neural networks. In GANNSA90 [1892], page ? † ga:Ball90a. [84] Lucia Ballerini. Genetic algorithms for automatic design of artificial neural networks. Tesi di laurea, University of Florence, 1993. †www /Ballerini ga:Ballerini93a. [85] N. R. Ball. Cognitive Maps in Learning Classifier Systems. PhD thesis, University of Reading, 1991. † ga:BallThesis. [86] J. Baxter. The evolution of learning algorithms for artificial neural networks. IOS Press, Amsterdam, 1993. †CCA 47949 ga:Baxter93a. [87] A. B. Cremers, K.-H. Becks, W. Burgard, and Andreas Hemker. A genetic algorithm for the reconstruction of physical events. In Teuvo Kohonen and Françoise Fogelman-Soulie, editors, Cognitiva 90 At the Crossroads of Artificial Intelligence, Cognitive Science, and Neuroscience, Proceedings of the Third COGNITIVA Symposium, pages 655–663, Madrid, 20.-23. November 1990. North-Holland. ga:Becks90. [88] Randall D. Beer and John C. Gallagher. Evolving dynamical neural networks for adaptive behavior. Adaptive Behavior, 1(?):92–122, 1992. †Beer93a ga:Beer92a. [89] John C. Gallagher and Randall D. Beer. A qualitative dynamical analysis of evolved locomotion control. In Roitblat et al. [1893], pages 71–80. ga:Beer93a. [90] Richard K. Belew and Michael Gherrity. Back propagation for the classifier system. In Schaffer [1894], pages 275–281. ga:Belew89b. [91] Richard K. Belew, John McInerney, and Nicol N. Schraudolph. Evolving networks: Using the genetic algorithm with connectionist learning. In Langton et al. [1895], pages 511–547. ga:Belew90b. [92] Richard K. Belew, John McInerney, and Nicol N. Schraudolph. Evolving networks: Using the genetic algorithm with connectionist learning. Technical Report No. CS90-174, University of San Diego, La Jolla, Computer Science and Engineering Department, 1990. ga:Belew90bb. [93] Richard K. Belew, John McInerney, and Nicol N. Schraudolph. Evolving networks: Using the genetic algorithm with connectionist learning. In Langton et al. [1895], pages 511–548. ga:Belew92a. [94] Richard K. Belew. Interposing an ontogenic model between genetic algorithms and neural networks. In J. Cowan, editor, Advances in Neural Information Processing (NIPS5), page ? Morgan Kaufmann, San Mateo, CA, 1993. †Forrest93d ga:Belew93a. [95] Matthew I. Bellgard and Chi Ping Tsang. Some experiments on the use of genetic algorithms in a Boltzmann machine. In 1991 IEEE International Joint Conference on Neural Networks (IJCANN91), volume 3, pages 2645–2652, Singapore, 18.-21. November 1991. IEEE, New York. * P52389 EI A098133/92 ga:Bellgard91a. [96] Aviv Bergman and M. Kerszberg. Breeding intelligent automata. In Proceedings of the First Annual Conference on Neural Networks, pages 63–70, ?, ? 1987. ? † ga:Bergman87. [97] S. T. Barnard and Aviv Bergman. Adaptation in signal spaces. In Schwefel and Männer [1896], pages 395–404. † ga:Bergman90. [98] Aviv Bergman. An evolutionary approach to designing neural networks. SIGBIO Newsletter, 12(2):47–51, 1992. ga:Bergman92a. [99] Pierre Bessière. Genetic algorithms applied to formal neural networks: Parallel genetic implementation of a Boltzmann machine and associated robotic experimentations. In Varela and Bourgine [1897], pages 310–314. ga:Bessiere91a. [100] Max Blanchet, Shuji Yoshizawa, and Sun ichi Amari. Modified Kohonen’s self-organizing feature map and its application to automatic sleep cycle recognition. In IJCNN’93 [276], pages 2476–2479. †EI M082911/94 ga:Blanchet93a. [101] J. McCullagh and K. Bluff. Genetic modification of a neural networks training data. In ?, editor, Proceedings 1993 The First New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems, pages 58–59, Dunedin (New Zealand), 24.-26. November 1993. IEEE Computer Society Press, Los Alamitos, CA. * CCA 45570/94 ga:Bluff93a. [102] Egber J. W. Boers and Herman Kuiper. Biological metaphors and the design of modular artificial neural networks. Master’s thesis, Leiden University, the Netherlands, 1992. †[867] ga:BoersMSThesis. [103] Hans-Michael Voigt, Joachim Born, and Ivan Santibáñez-Koref. Evolutionary structuring of artificial neural networks. Technical Report TR-93-002, Technische Universität der Berlin, Bionics and Evolution Techniques Laboratory, 1993. (ftp://ftp-bionik.fb10.tu-berlin.de/pub/papers/Bionik/tr-02-93. ps.Z) ga:Born93c. 66 Genetic algorithms and neural networks [104] Hans-Michael Voigt, Joachim Born, and Ivan Santibáñez-Koref. Structuring of artificial neural networks with generative grammars. In M. v. d. Meer, editor, Statusseminar des BMFT Neuroinformatik, pages 45–54, Schloss Maurach (Germany), 20.-21. September 1992. Projektträger informationstechnik des BMFT bei der DLR, Berlin. †Born ga:Born93e. [105] Stefan Bornholdt and Dirk Graudenz. General asymmetric neural networks and structure design by genetic algorithms. Technical Report DESY 91-046, Deutsches Elektronen-Synchrotron, Hamburg, 1991. †BackBib ga:Bornholdt91a. [106] Stefan Bornholdt and Dirk Graudenz. General asymmetric neural networks and structure design by genetic algorithms: A learning rule for temporal patterns. In 1993, International Conference on Systems, Man and Cybernetics, volume 2, pages 595–600, Le Touquet (France), 17.-20. October 1993. IEEE, New York. ga:Bornholdt93a. [107] M. Bos and H. T. Weber. Comparison of the training of neural networks for quantitative x-ray flourescence spectrometry by a genetic algorithm and backward error propagation. Analytica Chimica Acta, 247(1):97– 105, June 1991. ga:Bos91a. [108] Bryn V. Williams and David G. Bounds. Learning and evolution in populations of backprop networks. In ? [1898], pages 1139–1149. ga:Bounds93a. [109] R. Boyd and C. Glass. Interpreting ground-penetrating radar images using object-oriented neural, fuzzy, and genetic processing. In H. N. Nasr, editor, Ground Sensing, volume SPIE-1941, pages 169–181, Orlando, FL, 14. April 1993. The International Society for Optical Engineering. †P59354/93 ga:Boyd93a. [110] la P. de Brassinne. Genetic algorithms and learning of neural nets. Bull. Sci. Assoc. Ing. Electr. Inst. Electrotech. Montefiore, 106(1):41–58, 1993. (in French) * CCA 42888 ga:Brassinne93a. [111] Frank Z. Brill, Donald E. Brown, and Worthy N. Martin. Genetic algorithms for feature selection for counterpropagation networks. Technical Report IPC-TR-90-004, University of Virginia, Institute of Parallel Computations, Charlottesville, 1990. † ga:Brill90. [112] Frank Z. Brill, Donald E. Brown, and Worthy N. Martin. Fast genetic selection of features for neural network classifiers. IEEE Transactions on Neural Networks, 3(2):324–328, March 1992. ga:Brill92. [113] Innesa L. Bukatova. Evolutionary neurocomputer technology. Preprint ?, Academy of Sciences of the USSR, Institute of Radio Engineering and Electronics, Moscow, 1992. †Bukatova ga:Bukatova92b. [114] R. G. Hoptroff, T. J. Hall, and R. E. Burge. Experiments with a neural controller. In 1990 International Joint Conference on Neural Networks - IJCNN 90, volume 2, pages 735–740, San Diego, CA, 17.-21. June 1990. IEEE, New York. * ga:Burge90. [115] P. Arena, R. Caponetto, L. Fortuna, and M. G. Xibilia. Genetic algorithms to select optimal neural network topology. In Proceedings of the 35th Midwest Conference on Circuits and Systems, volume 2, pages 1381–1383, Washington, 9.-12. August 1992. IEEE. ga:Caponetto92a. [116] P. Arena, R. Caponetto, L. Fortuna, and M. G. Xibilia. M. L. P. optimal topology via genetic algorithms. In Albrecht et al. [1889], pages 670–674. ga:Caponetto93a. [117] Kevin Richard Caskey. Genetic algorithms and neural networks applied to manufacturing scheduling. PhD thesis, University of Washington, 1993. * DAI V. 54 N. 8 (Feb 94) ga:CaskeyThesis. [118] Thomas P. Caudell and Charles P. Dolan. Parametric connectivity: Training of constrained networks using genetic algorithms. In Schaffer [1894], pages 370–374. ga:Caudell89. [119] Thomas P. Caudell. Genetic algorithms as a tool for the analysis of adaptive resonance theory network training sets. In Schaffer and Whitley [125], pages 184–200. * CCA 60587/93 ga:Caudell92a. [120] Maureen Caudill. Evolutionary neural networks. AI Expert, 6(3):28–33, March 1991. ga:Caudill91a. [121] François E. Cellier. In Continuous System Modeling, chapter 14. Artificial neural networks and genetic algorithms, pages 623–701. Springer-Verlag, Berlin, 1991. ga:Cellier91a. [122] David J. Chalmers. The evolution of learning: An experiment in genetic connectionism. In D. S. Touretsky, J. L. Elman, T. J. Sejnowski, and G. E. Hinton, editors, Proceedings of the Connectionist Summer School, page ?, San Diego, CA, ? 1990. Morgan Kaufmann, San Mateo, CA. †[?] [1899] ga:Chalmers90. [123] C. H. Chu and C. R. Chow. A genetic algorithm approach to supervised learning for multilayered networks. In Proceedings of the World Congress on Neural Networks - WCNN ’93, volume IV, pages 744–747, Portland, OR, 11.-15. July 1993. Lawrence Erlbaum Ass., Inc., Hillsdale, NJ. ga:Chow93a. [124] Tibor Kozek, Tamás Roska, and Leon O. Chua. Genetic algorithm for CNN template learning. IEEE Transactions on Circuits and Systems — I, Fundamental Theory and Applications, 40(6):392–402, November 1993. ga:Chua93a. Bibliography 67 [125] J. David Schaffer and Darrell Whitley, editors. COGANN-92, International Workshop on Combinations of Genetic Algorithms and Neural Networks, Baltimore, MD, 6. June 1992. IEEE Computer Society Press, Los Alamitos, CA. † ga:COGANN92. [126] Andrew Colin. Neural networks and genetic algorithms for exchange rate forecasting. In ?, editor, Proceedings of the International Joint Conference on Neural Networks (IJCNN’92), volume ?, page ?, Beijing, August 1992. ? †Colin93a ga:Colin92a. [127] M. Compiani, D. Montanari, R. Serra, and G. Valastro. Classifier systems and neural networks. In E. R. Caianiello, editor, First Italian workshop: Parallel architectures and neural networks, pages 105–118, Teaneck, NJ, ? 1989. World Scientific. † ga:Compiani89b. [128] Michael Conrad, R. R. Kampfner, and K. G. Kirby. Neuronal dynamics and evolutionary learning. In Advances in cognitive science: Steps towards convergence, pages 169–189. Westview Press, Boulder, CO, 1988. † ga:Conrad88b. [129] K. G. Kirby and Michael Conrad. Bit-vector optimization algorithms for control of learning in neurons with second-messenger dynamics. In IEEE International Conference on Neural Nets, volume II, pages 55–62, ?, ? 1988. IEEE. † ga:Conrad88c. [130] C. Dagli and Sinchai Sittisathanchai. Genetic neuro-scheduler for job shop scheduling. Computers & Industrial Engineering, 25(1-4):267–270, 1993. †CCA 6856/94 ga:Dagli93a. [131] Ricardo Jose Machado and Armando Freitas da Rocha. Evolutive fuzzy neural networks. In Proceedings of the 1992 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), pages 493–500, San Diego, CA, 8.-12. March 1992. IEEE, New York. * EI 035270 ga:daRocha92a. [132] Lawrence Davis. Mapping neural networks into genetic algorithms. In Schaffer [1894], pages 375–378. ga:Davis89b. [133] David J. Montana and Lawrence Davis. Training feedforward neural networks using genetic algorithms. In N. S. Sridharan, editor, Eleventh International Joint Conference on Artificial Intelligence (IJCAI-89), pages 762–767, Detroit, MI, 20.-25. August 1989. Morgan Kaufmann, Palo Alto, CA. ga:Davis89c. [134] Tony Deboeck and Guido Deboeck. GenNet: Genetic optimization of neural nets for trading. Advanced Technology for Developers, 1(6):1–, October 1992. †Advanced ... index ga:Deboeck92a. [135] Guido Deboeck. How to build a hybrid trading system in a spreadsheet... in five easy steps. Advanced Technology for Developers, 2(?):1–19, April 1993. ga:Deboeck93a. [136] Franz A. Dill and Barry C. Deer. An exploration of genetic algorithms for the selection of connection weights in dynamical neural networks. In Proceedings of the IEEE 1991 National Aerospace and Electronics Conference NAECON 91, volume 3, pages 1111–1115, Dayton, OH, 20.-24. May 1991. IEEE, New York. * EI 098784/92 ga:Deer91a. [137] Hugo de Garis. ’compo’ conceptual clustering with connectionist competitive learning. In Proceedings of the First IEE International Conference on Artificial Neural Networks, pages 226–232, London, 16.-18. October 1989. IEE. ga:deGaris89a. [138] Hugo de Garis. Building artificial nervous systems using genetically programmed neural network modules. In Bruce Porter and Raymond Mooney, editors, Machine Learning: Proceedings of the Seventh International Conference, pages 132–139, University of Texas, 21. - 23. June 1990. Morgan Kaufmann Publishers, Inc. ga:deGaris90a. [139] Hugo de Garis. Genetic programming: artificial nervous systems, artificial embryos and embryological electronics. In Schwefel and Männer [1896], pages 117–123. ga:deGaris90b. [140] Hugo de Garis. Genetic programming: Building nanobrains with genetically programmed neural network module. In 1990 International Joint Conference on Neural Networks - IJCNN 90, volume 3, pages 511–516, San Diego, CA, 17.-21. June 1990. IEEE, New York. * ga:deGaris90c. [141] Hugo de Garis. Genetic programming: Building artificial nervous systems using genetically programmed neural network modules. In Proceedings of the 7th International Conference on Machine Learning, pages 132–139, ?, ? 1990. Morgan Kaufmann. † ga:deGaris90e. [142] Hugo de Garis. Genetic programming: Evolution of a time dependent neural network module which teaches a pair of stick legs to walk. In Luigia Carlucci Aiello, editor, ECAI 90 9th European Conference on Artificial Intelligence, pages 204–206, Stockholm, 6.-10. August 1990. Pitman Publishing, London. ga:deGaris90f. [143] Hugo de Garis. Brain building with GenNets. In ?, editor, Proceedings of the International Conference on Neural Networks (INNC-90-PARIS), volume ?, page ?, Paris, 9.-13. July 1990. Kluwer, Dordrecht, Netherlands. †de Garis ga:deGaris90h. 68 Genetic algorithms and neural networks [144] Hugo de Garis. Genetic neural nets can be dynamic too, you know! Summer 1990. †de Garis ga:deGaris90i. Neural Network Review, ?(?):?, [145] Hugo de Garis. Lizzy: The genetic programming of an artificial neural nervous system. In Teuvo Kohonen, Kai Mäkisara, Olli Simula, and Jari Kangas, editors, Artificial Neural Networks, Proceedings of the 1991 International Conference on Artificial Neural Networks (ICANN-91), volume 2, pages 1269–1272, Espoo (Finland), 24.-28. June 1991. North-Holland. ga:deGaris91b. [146] Hugo de Garis. GenNets: Genetically programmed neural nets: Using the genetic algorithm to train neural nets whose inputs and/or output vary in time. In 1991 IEEE International Joint Conference on Neural Networks (IJCANN91), pages 1391–1396, Singapore, 18.-21. November 1991. IEEE, New York. * EI A099159/92 ga:deGaris91c. [147] Hugo de Garis. Using the genetic algorithm to train time dependent behaviours in neural networks. In R. S. Michalski, G. Tecuci, and G. Fairfax, editors, Proceedings of the First International Workshop on Multistrategy Learning (MSL-91), pages 273–280, Harpers Ferry, WV, 7.-9. November 1991. Center for Artificial Intelligence, Fairfax, VA. †Fogel/bib ga:deGaris91e. [148] Hugo de Garis. Genetic control: Building artificial nervous system and artificial embryos. In ?, editor, 1991 Benelux Meeting on Systems and Control, volume ?, page ?, Blankenberge (Belgium), March 1991. ? †de Garis ga:deGaris91f. [149] Hugo de Garis. Brain building: The genetic programming of artificial nervous systems and artificial embryos. In O. M. Omidvar, editor, Prograss in Neural Networks, volume 4, page ? Ablex Publ. Corp., ?, 1991. †de Garis ga:deGaris91h. [150] Hugo de Garis. Exploring GenNet behaviours using genetic programming to explore quantitatively new behaviors in recurrent neural networks. In Proceedings of the IJCNN International Joint Conference on Neural Networks, volume III, pages 547–552, Baltimore, MD, 7.-11. June 1992. IEEE, New York. ga:deGaris92c. [151] Hugo de Garis. Artificial nervous systems: The genetic programming of production-rule-GenNet circuits. In ?, editor, Proceedings of the International Joint Conference on Neural Networks, volume ?, page ?, Beijing (China), November 1992. ? †de Garis ga:deGaris92e. [152] Hugo de Garis. Circuit of production rule GenNets the genetic programming of artificial nervous systems. In Albrecht et al. [1889], pages 699–705. ga:deGaris93b. [153] Tetsuya Higuchi, Tatsuya Niwa, Toshio Tanaka, Hitoshi Iba, Hugo de Garis, and Tatsumi Furuya. Evolving hardware with genetic learning: A first step towards building a Darwin machine. In Roitblat et al. [1893], pages 417–424. ga:deGaris93c. [154] Hugo de Garis. Neurite networks: The genetic programming of cellular automata based neural nets which GROW. In IJCNN’93 [276], pages 2921–2924. ga:deGaris93e. [155] Hugo de Garis. Incremental evolution of neural nets genetic programming in incremental steps. In Proceedings of the World Congress on Neural Networks WCNN’93, volume II, pages 447–450, Portland, OR, 11.-15. July 1993. Lawrence Erlbaum Ass., Inc., Hillsdale, NJ. ga:deGaris93j. [156] Hugo de Garis. Incremental genetic programming, multistrategy learning in neural nets. In ?, editor, Proceedings of the Multistrategy Learning Workshop (MSL’93), volume ?, page ?, West Virginia, May 1993. ? †de Garis ga:deGaris93k. [157] Hugo de Garis. Neurite networks: The genetic programming of cellular automata based neural nets which grow. In ?, editor, Proceedings of the International Joint Conference on Neural Networks, volume ?, page ?, Nagoya (Japan), October 1993. ? †de Garis ga:deGaris93l. [158] Hugo de Garis. Artificial life: Growing an artificial brain with a million neural net modules inside a trillion cell cellular automata machine. In ?, editor, Proceedings of the 4th International Symposium on Micro Machine & Human Science, volume ?, page ?, Nagoya (Japan), October 1993. ? †de Garis ga:deGaris93m. [159] R. C. Eberhart and R. W. Dobbins. Designing neural network explanation facilities using genetic algorithms. In 1991 IEEE International Joint Conference on Neural Networks (IJCANN91), volume 3, pages 1758–1363, Singapore, 18.-21. November 1991. IEEE, New York. * P52389 EI A098469/92 ga:Dobbins91a. [160] M. Tadel, L. Grabensek, and Andrej Dobnikar. Neural networks without design – evolution with genetic algorithms and genotypes of variable length. Internal Report ?, LASPP-FER, Ljubljana, Slovenia, 1993. (in Slovenian) †[987] ga:Dobnikar93a. Bibliography 69 [161] Nigel Dodd. Optimization of network structure using genetic techniques. In 1990 International Joint Conference on Neural Networks - IJCNN 90, volume 3, pages 965–970, San Diego, CA, 17.-21. June 1990. IEEE, New York. * EI A096719/91 ga:Dodd90. [162] Nigel Dodd. Optimization of neural-network structure using genetic techniques. In G. Rzevski and R. A. Adey, editors, Applications of Artificial Intelligence in Engineering, Proceedings of the 6th International Conference on Artificial Intelligence in Engineering (AIENG91), volume VI, pages 939–944, Oxford, June 1991. Elsevier Science Publishing, New York. † ga:Dodd91. [163] W. B. Dress and J. R. Kinsley. A Darwinian approach to artificial neural systems. In Proceedings of the 1987 IEEE International Conference on Systems, Man, and Cybernetics, pages 572–577, ?, ? 1987. IEEE. † ga:Dress87a. [164] W. B. Dress. High-performance neural networks. J. Forth Appl. Res., 5(1):137–140, 1987. * EI A110388/88 ga:Dress87b. [165] David Rogers. Predicting weather using a genetic memory: a combination of Kanerva’s sparse distributed memory with Holland’s genetic algorithms. In Touretzky [455], pages 455–464. ga:DRogers90a. [166] D. White and P. Ligomenides. GANNet: a genetic algorithm for optimizing topology and weights in neural network design: the first step in finding a neural network solution. In Proceedings of the International Workshop on Artificial Neural Networks (IWANN’93), pages 322–327, Sitges (Spain), 9.-11. June 1993. Springer-Verlag, Berlin. * CCA 17368/93 ga:DWhite93a. [167] Dan Wood. A von Neumann approach to a genotype expression in a neural animat. In Meyer and Wilson [1900], pages 427–432. ga:DWood91a. [168] M. Eaton. Process control using genetically trained neural networks. Journal of Microcomputer Applications, 16(2):137–145, April 1993. * CA 5529 Vol. 37 No. 7/8; ACM/93 ga:Eaton93a. [169] R. C. Eberhart. The role of genetic algorithms in neural network query-based learning and explanation facilities. In Schaffer and Whitley [125], pages 169–183. * CCA 58172 ga:Eberhart92a. [170] Rolf Eckmiller, Georg Hartmann, and Gert Hauske, editors. Parallel Processing in Neural Systems and Computers. Elsevier Science Publisher B.V. , Amsterdam, Düsseldorf (Germany), 19.-21. March 1990. † ga:Eckmiller90book. [171] John G. Elias. Genetic generation of connection patterns for a dynamic artificial neural network. In Schaffer and Whitley [125], pages 38–54. * CCA 58169/93 ga:Elias92a. [172] John G. Elias and Ben Chang. A genetic algorithm for training networks with artificial dendritic trees. In Proceedings of the IJCNN International Joint Conference on Neural Networks, volume I, pages 652–657, Baltimore, MD, 7.-11. June 1992. IEEE, New York. ga:Elias92b. [173] John G. Elias. Target tracking using impulsive analog circuits. In ?, editor, Applications of Artificial Neural Networks III, volume SPIE-1709, pages 338–350, Orlando, FL, 21. -24. April 1992. The International Society for Optical Engineering. †EEA 28322/93 ga:Elias92c. [174] Elie Sanchez. Genetic algorithms, neural networks and fuzzy logic systems. In Proceedings of the 2nd International Conference on Fuzzy Logic and Neural Networks (IIZUKA’92), volume 1, pages 17–19, Iizuka (Japan), 17.-22. July 1992. Fuzzy Logic Systems Institute. ga:ESanchez92a. [175] J. F. Falcon. Simulated evolution of modular networks. In Proceedings of the International Workshop on Artificial Neural Networks (IWANN’91), pages 204–211, Granada (Spain), 17.-19. September 1991. Springer-Verlag, Berlin. * EEA 69782/92 ga:Falcon91a. [176] David S. Feldman. Fuzzy network synthesis with genetic algorithms. In Forrest [1901], pages 312–317. ga:Feldman93a. [177] J. J. Ferguson and S. I. Hruska. Training and validating expert networks: sample selection strategies using genetic algorithms. In ?, editor, Proceedings of the 5th Florida Artificial Intelligence Symposium, pages 15–18, Forth Lauderdale, FL, 7.-10. April 1992. Florida AI Res. Soc., St. Petersburg. * CCA 72001/94 ga:Ferguson92a. [178] Dario Floreano. Emergence of nest-based foraging strategies in ecosystems of neural networks. In Roitblat et al. [1893], pages 410–416. ga:Floreano93a. [179] Terence C. Fogarty. Using the genetic algorithm to adapt intelligent systems. pages 248–251. IOS Press, Amsterdam, 1990. ga:Fogarty90b. 70 Genetic algorithms and neural networks [180] A. V. Sebald and David B. Fogel. Design of slayr neural networks using evolutionary programming. In Ray R. Chen, editor, Proceedings of the Twenty-Fourth Asilomar Conference on Signals, Systems & Computers, volume 2, pages 1020–1024, Pacific Grove, CA, 5.-7. November 1990. The Computer Society of IEEE/Maple Press. ga:Fogel90c. [181] David B. Fogel. An information criterion for neural network selection. In Ray R. Chen, editor, Proceedings of the Twenty-Fourth Asilomar Conference on Signals, Systems & Computers, volume 2, pages 998– 1002, Pacific Grove, CA, 5.-7. November 1990. The Computer Society of IEEE/Maple Press. †Fogel/bib ga:Fogel90e. [182] David B. Fogel, Lawrence J. Fogel, and Vincent W. Porto. Evolving neural networks. Biological Cybernetics, 63(6):487–493, 1990. †Fogel/bib ga:Fogel90g. [183] David B. Fogel. Selecting an optimal neural network. In A. C. Weaver, editor, IECON’90, 16th Annual Conference of the IEEE Industrial Electronics Society, pages 1211–1214, Pacific Grove, CA, November 1990. IEEE. †Fogel/bib ga:Fogel90i. [184] David B. Fogel and A. V. Sebald. Use of evolutionary programming in the design of neural networks for artifact detection. In Proceedings of IEEE EMBS, page ?, Philadelphia, PA, May 1990. IEEE. †Fogel/bib ga:Fogel90k. [185] David B. Fogel and A. V. Sebald. Training neural networks through evolutionary adaptation. In International AMSE Conference on Neural Network Methodologies and Applications, page ?, San Diego, CA, ? 1990. ? †Fogel/bib ga:Fogel90l. [186] David B. Fogel, Lawrence J. Fogel, and Vincent W. Porto. Evolutionary programming for training neural networks. In Proceedings of the International Joint Conference on Neural Networks 1990, pages 601–605, San Diego, CA, June 1990. IEEE Press, New York. †Fogel ga:Fogel90m. [187] A. V. Sebald, J. Schlenzig, and David B. Fogel. Minimax design of CMAC encoded neural network controllers using evolutionary programming. In Ray R. Chen, editor, Proceedings of the Twenty-Fifth Asilomar Conference on Signals, Systems & Computers, pages 551–555, Pacific Grove, CA, 1991. IEEE. †Fogel/bib ga:Fogel91ab. [188] David B. Fogel, Lawrence J. Fogel, and Vincent W. Porto. Evolutionary methods for training neural networks. In Proceedings of Conference on Neural Networks for Ocean Engineering, pages 317–328, Washington D.C., July 1991. IEEE Press, New York. †Fogel/bib ga:Fogel91b. [189] David B. Fogel. An information criterion for optimal neural network selection. IEEE Transactions on Neural Networks, 2(5):490–497, 1991. †Fogel/bib ga:Fogel91e. [190] A. V. Sebald, J. Schlenzig, and David B. Fogel. Minimax design of CMAC encoded neural controllers for systems with variable time delay. In Fogel and Atmar [1890], pages 120–126. †Fogel/bib ga:Fogel92e. [191] A. V. Sebald and David B. Fogel. Design of fault-tolerant neural networks for pattern classification. In Fogel and Atmar [1890], pages 90–99. †Fogel/bib ga:Fogel92j. [192] David B. Fogel and Lawrence J. Fogel. Method and apparatus for training a neural network using evolutionary programming, 1992. (U. S. patent no. 5,214,746. Issued May 25 1993) † ga:Fogel92m. [193] David B. Fogel. Using evolutionary programming to create neural networks that are capable of playing tic-tac-toe. In IEEENN93 [275], pages 875–880. ga:Fogel93a. [194] Richard S. Forsyth. Neural learning algorithms: some empirical trials. In IEE Colloquium on ‘Machine Learning’, volume IEE Digest No. 1990/?, pages 8/1–8/7, London, ? 1990. IEE, London. ga:Forsyth90a. [195] Mark Foy. Linking genetic algorithms with connectionist models. Technical Report GE 393 report, University of Illinois at Urbana-Champaign, 1991. ga:Foy91. [196] M. Foy and C. Uhrik. Exploiting domain knowledge, neural networks and genetic algorithms to harvest traffic simulation results. In Knowledge Based Hybrid Systems, volume 11 of IFIP Transactions B Applied Technology, pages 119–130, Budapest (Hungary), 20.-22. April 1993. Elsevier Science Publ. B. V., Amsterdam. * CCA 932/94 P60645/94 EI M158943/94 ga:Foy93a. [197] Bernd Freisleben and Michael Härtfelder. Optimization of genetic algorithms by genetic algorithms. In Albrecht et al. [1889], pages 392–399. ga:Freisleben93a. [198] David J. Janson and James F. Frenzel. Application of genetic algorithms to the training of higher order neural networks. Journal of Systems Engineering, 2(4):272–276, 1992. †CCA 25393/93 ga:Frenzel92a. Bibliography 71 [199] David J. Janson and James F. Frenzel. Training product unit neural networks with genetic algorithms. In Firooz A. Sadjadi, editor, Adaptive and Learning Systems, volume SPIE-1706, pages 32–38, Orlando, FL, 20. -21. April 1992. The International Society for Optical Engineering. * EI 147080/93 CCA 34484/94 ga:Frenzel92b. [200] David J. Janson and James F. Frenzel. Training product unit neural networks with genetic algorithms. IEEE Expert, 8(5):26–33, October 1993. ga:Frenzel93a. [201] James F. Frenzel. Genetic algorithms. IEEE Potentials, 12(3):21–24, October 1993. †CCA 51330/94 EEA 54696/94 ga:Frenzel93b. [202] Takanori Shibata, Toshio Fukuda, and Tadashi Kohno. Supervised learning for recurrent neural networks by genetic algorithm. In Proceedings of the IJCNN’92, volume 1, pages 413–418, Beijing, August 1992. ? †Fukuda93f ga:Fukuda92c. [203] Toshio Fukuda, Tadashi Kohno, and Takanori Shibata. Heuristic learning by genetic algorithm for recurrent neural network. In EFTA ’93, 2nd International IEEE Workshop on Emerging Technologies and Factory Automation, pages 71–77, Cairns (Australia), 27.-29. September 1993. IEEE. †conf. program ga:Fukuda93b. [204] Toshio Fukuda, Hideyuki Ishigami, Takanori Shibata, and Fumihito Arai. Auto fuzzy tuning having minimum structure by using genetic algorithm and delta rule. In EFTA ’93, 2nd International IEEE Workshop on Emerging Technologies and Factory Automation, pages 86–94, Cairns (Australia), 27.-29. September 1993. IEEE. †CCA 44332/95 ga:Fukuda93c1. [205] Takanori Shibata, Toshio Fukuda, and Kazuo Tanie. Nonlinear backlash compensation using recurrent neural network - unsupervised learning by genetic algorithm -. In IJCNN’93 [276], pages 742–745. ga:Fukuda93f. [206] Takanori Shibata, Toshio Fukuda, and Kazuo Tanie. Fuzzy critic for robotic motion planning by genetic algorithm in hierarchical intelligent control. In IJCNN’93 [276], pages 770–773. ga:Fukuda93g. [207] Takanori Shibata, Toshio Fukuda, and Kazuo Tanie. Synthesis of fuzzy, artificial intelligence, neural networks, and genetic algorithm for hierarchical intelligent control. In IJCNN’93 [276], pages 2869–2872. ga:Fukuda93h. [208] Toshio Fukuda and Hideyuki Ishigami. Structure optimization of fuzzy neural network using genetic algorithm. In Proceedings of the 5th IFSA Congress (IFSA’93), volume II, pages 961–967, Seoul (South Korea), July 1993. ? †Fukuda93h ga:Fukuda93i. [209] Toshio Fukuda, Hideyuki Ishigami, Fumihito Arai, and Takanori Shibata. Recognition and counting method of biological cells on expert system (4th report, optimizing the initial values for neural network using genetic algorithm). Nippon Kikai Gakkai Ronbunshu C Hen, 59(561):152–158, May 1993. (in Japanese) * EI 132727/93 ga:Fukuda93r. [210] Toshio Fukuda, Tadashi Kohno, and Takanori Shibata. Dynamic memory by recurrent neural network and its learning by genetic algorithm. In Proceedings of the 32nd IEEE Conference on Decision and Control, volume 3, pages 2815–2820, San Antonio, TX, 15.-17. December 1993. IEEE Control Systems Society. ga:Fukuda93t. [211] Minoru Fukumi and Sigeru Omatu. Designing a neural network for coin recognition by a genetic algorithm. In IJCNN’93 [276], pages 2109–2112. ga:Fukumi93a. [212] Minoru Fukumi and Sigeru Omatu. Designing an architecture of a neural network for coin recognition by a genetic algorithm. Transactions of the Institute of Electrical Engineers of Japan C, 113-D(12):1403–1409, December 1993. (in Japanese) * CCA 51639/94 ga:Fukumi93b. [213] Geoffrey F. Miller, Peter M. Todd, and Shailesh U. Hegde. Designing neural networks using genetic algorithms. In Schaffer [1894], pages 379–384. ga:GFMiller89a. [214] Peter M. Todd and Geoffrey F. Miller. Exploring adaptive agency III: Simulating the evolution of habituation and sensitization. In Schwefel and Männer [1896], pages 307–313. † ga:GFMiller90. [215] Peter M. Todd and Geoffrey F. Miller. Exploring adaptive agency II: Simulating the evolution of associative learning. In Meyer and Wilson [1900], pages 306–315. ga:GFMiller91b. [216] Pierre Yves Glorennec. Application of genetic algorithms for the optimization of the learning functions of a fuzzy neural net. In Les Applications Des Ensembles Flous (Applications of Fuzzy Sets), pages 219– 226, Nimes (France), 2.-3. November 1992. EC2, Nanterre Cedex (France). (in French) * CCA 9653/93 ga:Glorennec92a. 72 Genetic algorithms and neural networks [217] Frédéric C. Gruau. Cellular encoding of genetic neural networks. Technical Report Technical Report 92-21, Ecole Normale Supérieure de Lyon, Laboratoire de l’Informatique du Parallélisme, 1992. †McGregor93a Koza ga:Gruau92a. [218] Frédéric C. Gruau. Genetic synthesis of Boolean neural networks with a cell rewriting developmental process. In Schaffer and Whitley [125], pages 55–74. * Koza ga:Gruau92b. [219] Frédéric C. Gruau. A learning and pruning algorithm for genetic Boolean neural networks. In Proceedings of the European Symposium on Artificial Neural Networks (ESANN’93), pages 57–63, Brussels (Belgium), 7.-9. April 1993. D Facto, Brussels. †CCA 1146/94 ga:Gruau93e. [220] Zhichao Guo. Using genetic algorithms to select inputs for neural networks. In Schaffer and Whitley [125], pages 223–234. * EEA 71377/93 ga:Guo92a. [221] Zhichao Guo. Nuclear power plant fault diagnostics and thermal performance studies using neural networks and genetic algorithms. PhD thesis, University of Tennessee, 1992. * DAI 53/7 ga:GuoThesis. [222] Gerhard Weiß. Combinings neural and evolutionary learning: Aspects and approaches. Technical Report Technical Report FKI-132-90, Technische Universität München, 1990. † ga:GWeiss90. [223] Ari Hämäläinen. GA and neural networks. In Jarmo T. Alander, editor, Proceedings of the First Finnish Workshop on Genetic Algorithms and their Applications, volume TKO-A30 of Research Reports. Espoo (Finland), 4.-5. November 1992 1993. GA:Hamalainen93a. [224] Peter J. B. Hancock. Gannet: Design of a neural network for face recognition by genetic algorithm. In GANNSA90 [1892], page ? †Fogel/bib ga:Hancock90a. [225] Peter J. B. Hancock. Recombination operators for the design of neural nets by genetic algorithm. In Männer and Manderick [1891], pages 441–450. † ga:Hancock92a. [226] Peter J. B. Hancock. Pruning neural nets by genetic algorithm. In I. Aleksander and J. Taylor, editors, Artificial Neural Networks 2, Proceedings of the 1992 International Conference on Artificial Neural Networks (ICANN-92), volume 2, pages 991–994, Brighton, (UK), 4.-7. September 1992. Elsevier Science Publ. B. V., Amsterdam. ga:Hancock92b. [227] Peter J. B. Hancock. Genetic algorithms and permutation problems: A comparison of recombination operators for neural net structure specification. In Schaffer and Whitley [125], pages 108–122. * Fogel/bib ga:Hancock92c. [228] Peter J. B. Hancock. Coding strategies for genetic algorithms and neural nets. PhD thesis, University of Stirling, Department of Computing Science and Mathematics, 1992. †Fogel/bib ga:HancockThesis. [229] B. L. M. Happel and J. M. J. Murre. Designing modular network architectures using a genetic algorithm. In I. Aleksander and J. Taylor, editors, Artificial Neural Networks 2, Proceedings of the 1992 International Conference on Artificial Neural Networks (ICANN-92), volume 2, pages 1215–1218, Brighton, England, 4.-7. September 1992. Elsevier Science Publ. B. V., Amsterdam. ga:Happel92a. [230] Aloke Guha, Steven Alex Harp, and Tariq Samad. Genetic synthesis of neural networks. Technical Report No. CSDD-88-4852-CC-1, Honeywell-Corporate Systems, Development Division, Golden Valley, MN, 1988. † ga:Harp88. [231] Steven Alex Harp, Tariq Samad, and Aloke Guha. Towards the genetic synthesis of neural networks. In Schaffer [1894], pages 360–369. ga:Harp89a. [232] Aloke Guha, Steven Alex Harp, and Tariq Samad. The genetic synthesis of neural networks. Technical Report CSDD-89-14852-2, Honeywell-Corporate Systems, Development Division, Golden Valley, MN, 1989. † ga:Harp89b. [233] Steven Alex Harp, Tariq Samad, and Aloke Guha. Designing application-specific neural networks using the genetic algorithm. In Touretzky [455], pages 447–454. ga:Harp90. [234] Steven Alex Harp and Tariq Samad. Genetic synthesis of neural network architecture. chapter 15, pages 202–221. 1991. ga:Harp91a. [235] Steven Alex Harp and Tariq Samad. Genetic optimization of self-organizing feature maps. In Proceedings of International Joint Conference on Neural Networks, volume I, pages 341–346, Seattle, WA, 8.-12. July 1991. IEEE Press. * EI A029430/92 ga:Harp91b. [236] Steven Alex Harp and Tariq Samad. Optimizing neural networks with genetic algorithms. In Proceedings of the American Power Conference, volume 54:2, pages 1138–1143, Chicago, IL, 1992. Illinois Institute of Technology, Chicago, IL. * P54958 CCA 31370/93 EI 077605/93 ga:Harp92a. Bibliography 73 [237] Steven Alex Harp and Tariq Samad. Optimizing neural networks with genetic algorithms. In D. J. Sobajic, editor, Neural Networks Computing for the Electric Power Industry, pages 41–46, Stanford, CA, 17.-19. August 1992. Lawrence Erlbaum Assoc. Publ., Hillsdale. †P61000/94 ga:Harp92b. [238] Aloke Guha, Steven Alex Harp, and Tariq Samad. Genetic algorithm synthesis of neural networks, 1992. (U. S. patent no. 5,140,530. Issued August 18 1992) ga:Harp92c. [239] Inman Harvey. ga:Harvey91b. The artificial evolution of behaviour. In Meyer and Wilson [1900], pages 400–408. [240] Inman Harvey, Philip Husbands, and David T. Cliff. Issues in evolutionary robotics. Technical Report CSRP219, University of Sussex, School of Cognitive and Computing Sciences, 1992. (also as [250]; ftp: //ftp.cogs.susx.ac.uk/pub/reports/csrp/csrp219.ps.Z) ga:Harvey92c. [241] David T. Cliff, Philip Husbands, and Inman Harvey. Evolving visually guided robots. Technical Report CSRP220, University of Sussex, School of Cognitive and Computing Sciences, 1992. (also as [249]; ftp: //ftp.cogs.susx.ac.uk/pub/reports/csrp/csrp220.ps.Z) ga:Harvey92d. [242] David T. Cliff, Inman Harvey, and Philip Husbands. Incremental evolution of neural network architechtures for adaptive behaviour. Technical Report CSRP256, University of Sussex, School of Cognitive and Computing Sciences, 1992. (also as [247]; ftp://ftp.cogs.susx.ac.uk/pub/reports/csrp/csrp256.ps.Z) ga:Harvey92db. [243] David T. Cliff, Philip Husbands, and Inman Harvey. Analysis of evolved sensory-motor controllers. Technical Report CSRP264, University of Sussex, School of Cognitive and Computing Sciences, 1992. (also as [251]; ftp://ftp.cogs.susx.ac.uk/pub/reports/csrp/csrp264.ps.Z) ga:Harvey92e. [244] Philip Husbands, Inman Harvey, and David T. Cliff. Analysing recurrent dynamical networks evolved for robot control. Technical Report CSRP265, University of Sussex, School of Cognitive and Computing Sciences, 1992. (also as [253]; ftp://ftp.cogs.susx.ac.uk/pub/reports/csrp/csrp265.ps.Z) ga:Harvey92f. [245] Inman Harvey, Philip Husbands, and David T. Cliff. Genetic convergence in a species of evolved robot control architecture. Technical Report CSRP267, University of Sussex, School of Cognitive and Computing Sciences, 1992. (also as [254]; ftp://ftp.cogs.susx.ac.uk/pub/reports/csrp/csrp267.ps.Z) ga:Harvey92g. [246] David T. Cliff, Philip Husbands, and Inman Harvey. Evolving recurrent dynamical networks for robot control. In Albrecht et al. [1889], pages 428–435. ga:Harvey93a. [247] David T. Cliff, Philip Husbands, and Inman Harvey. Incremental evolution of neural network architectures for adaptive behaviour. In Proceedings of the European Symposium on Artificial Neural Networks (ESANN’93), pages 39–44, Brussels (Belgium), 7.-9. April 1993. D Facto, Brussels. ga:Harvey93b. [248] David T. Cliff, Philip Husbands, and Inman Harvey. Incremental evolution of neural network architectures for adaptive behaviour. Technical Report Report CSRP256, University of Sussex, School of Cognitive and Computing Science, 1993. (ftp://ftp.cogs.susx.ac.uk/pub/reports/csrp/csrp256.ps.Z) * Harvey ga:Harvey93bb. [249] David T. Cliff, Philip Husbands, and Inman Harvey. Evolving visually guided robots. In Roitblat et al. [1893], pages 374–383. also as [241] ga:Harvey93c. [250] David T. Cliff, Philip Husbands, and Inman Harvey. Issues in evolutionary robotics. In Roitblat et al. [1893], pages 364–373. also as [240] ga:Harvey93d. [251] David T. Cliff, Philip Husbands, and Inman Harvey. Analysis of evolved sensory-motor controllers. In ? [1898], pages 192–204. also as [243] ga:Harvey93e. [252] Philip Husbands, Inman Harvey, and David T. Cliff. An evolutionary approach to situated AI. In Proceedings of the 9th Bi-annual Conference of the Society for the Study of Artificial Intelligence and the Simulation of Behaviour (AISB 93), pages 61–70, Birmingham (UK), 29. March - 2. April 1993. IOS Press, Amsterdam. †CCA 19250/93 ga:Harvey93f. [253] Philip Husbands, Inman Harvey, and David T. Cliff. Analysing recurrent dynamical networks evolved for robot control. In ?, editor, Proceedings of the 3rd IEE International Conference on ANNs, page ?, ?, ? 1993. IEE Press. also as [244] † ga:Harvey93g. [254] Inman Harvey, Philip Husbands, and David T. Cliff. Genetic convergence in a species of evolved robot control architecture. In Forrest [1901]. also as [245] ga:Harvey93ha. 74 Genetic algorithms and neural networks [255] David T. Cliff, Inman Harvey, and Philip Husbands. Evolved recurrent dynamical networks use noise. In Stan Gielen and Bert Kappen, editors, ICANN’93 Proceedings of the International Conference on Artificial Neural Networks, pages 285–288, Amsterdam (The Netherlands), 13.-16. September 1993. Springer-Verlag, Berlin. ga:Harvey93i. [256] David T. Cliff, Inman Harvey, and Philip Husbands. General visual robot controller networks via artificial evolution. In D. Casasent, editor, Intelligent Robots and Computer Vision XII: Algorithms and Techniques, volume SPIE-2055, page ?, Boston, MA, 7. -10. September 1993. The International Society for Optical Engineering. ga:Harvey93k. [257] David T. Cliff, Inman Harvey, and Philip Husbands. General visual robot controller networks via artificial evolution. Technical Report Report CSRP318, University of Sussex, School of Cognitive and Computing Science, 1993. (also as [256]; ftp://ftp.cogs.susx.ac.uk/pub/reports/csrp/csrp318.ps.Z) ga:Harvey93ka. [258] Mohamad H. Hassoun and Jing Song. Hybrid genetic/gradient search for multilayer perceptron training. Opt. Mem. Neural Netw. (USA), 2(1):1–15, 1993. * CCA 12773/93 ga:Hassoun93a. [259] Mohamad H. Hassoun and Jing Song. Multilayer perceptron learning via genetic search for hidden layer activations. In Proceedings of the World Congress on Neural Networks WCNN’93, volume III, pages 437– 444, Portland, OR, 11.-15. July 1993. Lawrence Erlbaum Ass., Inc., Hillsdale, NJ. ga:Hassoun93b. [260] Jochen Heistermann. Learning in neural nets by genetic algorithms. In Eckmiller et al. [170], pages 165–168. † ga:Heistermann90a. [261] Jochen Heistermann and H. Eckardt. Parallel algorithms for learning in neural networks with evolution strategy. In D. J. Evans, G. R. Joubert, and F. J. Peters, editors, Parallel Computing 89, pages 275–280, ?, ? 1990. Elsevier Science Publishers. † ga:Heistermann90b. [262] Jochen Heistermann. The application of a genetic approach as an algorithm for neural networks. In Schwefel and Männer [1896], pages 297–301. † ga:Heistermann91a. [263] Jochen Heistermann. A mixed genetic approach to the optimization of neural controllers. In Patrick Dewilde and Joos Vandewalle, editors, CompEuro 1992 Proceedings, Computer Systems and Software Engineering, 6th Annual European Computer Conference, pages 459–464, The Hague, 4.-8. May 1992. IEEE Computer Society, IEEE Computer Society Press. ga:Heistermann92a. [264] Michael Herdy. Evolutionsstrategisches Belehren von Neuronalen Netzen zur Verbesserung der Resistenz gegen Ausfall einzelner Neuronen. In E. Köhler, editor, 36. Internationales wissenschaftliches Kolloquium, pages 625–630, Ilmenau (Germany), 21.-24. October 1991. Technische Universität Ilmenau. †Back/bib/unp ga:Herdy91a. [265] Adhanom A. Fekadu, Evor L. Hines, and Julian W. Gardner. Genetic algorithm design of neural net based electronic nose. In Albrecht et al. [1889], pages 691–698. ga:Hines93a. [266] Kenneth J. Hintz and J. J. Spofford. Evolving a neural network. In Proceedings of the 5th IEEE International Symposium on Intelligent Control, pages 479–484, Philadelphia, PA, 5.-7. September 1990. IEEE. * ga:Hintz90. [267] K.-U. Höffgen, H. P. Siemon, and A. Ultsch. Genetic improvement of feedforward nets for approximating functions. In Schwefel and Männer [1896], pages 302–306. † ga:Hoffgen90. [268] Abdollah Homaifar and Shanguchuan Guan. Training weights of neural networks by genetic algorithms and messy genetic algorithms. In M. H. Hamza, editor, Proceedings of the Second IASTED International Symposium. Expert Systems and Neural Networks, pages 74–77, Hawaii, HI, 15.-17. August 1990. Acta Press, Anaheim, CA. * CCA 62878/92 ga:Homaifar90a. [269] Mark C. Spittle and David H. Horrocks. Genetic algorithms and reduced complexity neural networks. In Proceedings of the IEE/IEEE Workshop on Natural Algorithms in Signal Processing, page ?, Essex (UK), 14.-16. November 1993. IEEE. †GAdigest.v7n29 ga:Horrocks93b. [270] Martin Hulin. ga:Hulin92a. chapter 15: Structure evolution in neural systems, pages 395–411. 1992. †BackBib [271] Shih-Lin Hung. Neural network and genetic learning algorithms for computer-aided design and pattern recognition. PhD thesis, The Ohio State University, 1992. * DAI 53/11 ga:HungThesis. [272] Yoshiaki Ichikawa. Evolution of neural networks and application to motion control. In Proceedings of IEEE International Conference on Intelligent Motion Control, pages 239–245, ?, ? 1990. IEEE. † ga:Ichikawa90a. Bibliography 75 [273] Yoshiaki Ichikawa and Toshiyuki Sawa. Neural network applications for direct feedback controllers. IEEE Transactions on Neural Networks, 3(2):224–231, March 1992. ga:Ichikawa92a. [274] Yoshiaki Ichikawa and Yoshikazu Ishii. Retaining diversity of genetic algorithms for multivariable optimization and neural network learning. In IEEENN93 [275], pages 1110–1114. ga:Ichikawa93a. [275] 1993 IEEE International Conference on Neural Networks, San Francisco, CA, 28. March - 1. April 1993. IEEE. ga:IEEENN93. [276] IJCNN’93-NAGOYA Proceedings of 1993 International Joint Conference on Neural Networks, Nagoya (Japan), 25.-29. October 1993. IEEE. ga:IJCNN93. [277] Jarmo T. Alander. Neural darwinism / Edelman. In Olli Simula, editor, Natural and Artificial Parallel Computation. Helsinki University of Technology, Faculty of Information Technology, Laboratory of Computer and Information Science, 1991. GA:INFO91. [278] Laurent Atlan and Jean-Arcady Meyer. Genetic programming applied to neural network design. Technical Report BioInfo 91-01, Ecole Normale Superiore, Groupe de BioInformatique, 1991. †Meyer ga:JAMeyer91b. [279] E. DeRouin and J. Brown. Alternative learning methods for training neural network classifiers. In ?, editor, Science of Artificial Neural Networks, volume SPIE-1710, pages 474–483, Orlando, FL, 21. -234 April 1992. The International Society for Optical Engineering. * EEA 30740/93 ga:JBrown92a. [280] Jose Gonzales-Seco. A genetic algorithm as the learning procedure for neural networks. In Proceedings of the IJCNN International Joint Conference on Neural Networks, volume I, pages 835–840, Baltimore, MD, 7.-11. June 1992. IEEE, New York. ga:JGonzalez-S92. [281] R. J. Mitchell, J. M. Bishop, and W. Low. Using a genetic algorithm to find the rules of a neural network. In Albrecht et al. [1889], pages 664–669. ga:JMBishop93a. [282] J. M. Bishop, M. J. Bushnell, A. Usher, and S. Westland. Genetic optimisation of neural network architectures for colour recipe prediction. In Albrecht et al. [1889], pages 719–725. ga:JMBishop93b. [283] I. M. Oliver, D. J. Smith, and J. R. C. Holland. A study of permutation crossover operators on the traveling salesman problem. In John J. Grefenstette, editor, Genetic Algorithms and their Applications: Proceedings of the Second International Conference on Genetic Algorithms and Their Applications, pages 224–230, MIT, Cambridge, MA, 28. - 31. July 1987. Lawrence Erlbaum Associates: Hillsdale, New Jersey. ga:JRCHolland87. [284] Angel DeCegama and Jeff Smith. Neural networks and genetic algorithms for combinatorial optimization of sensor data fusion. In Vibeke Libby and Ivan Kadar, editors, Signal Processing, Sensor Fusion, and Target Recognition, volume SPIE-1699, pages 108–115, Orlando, FL, 20. -22. April 1992. The International Society for Optical Engineering. ga:JSmith92. [285] Nagesh Kadaba and Kendall E. Nygard. Improving the performance of genetic algorithms in automated discovery of parameters. In Bruce Porter and Raymond Mooney, editors, Machine Learning: Proceedings of the Seventh International Conference, pages 140–148, University of Texas, 21. - 23. June 1990. Morgan Kaufmann Publishers, Inc. ga:Kadaba90. [286] Nagesh Kadaba. Xroute: A knowledge-based routing system using neural networks and genetic algorithms. PhD thesis, North Dakota State University of Agriculture and Applied Sciences, Fargo, 1990. ga:KadabaThesis. [287] R. R. Kampfner. Generalization in evolutionary learning with enzymatic neuron-based systems. In M. Kochen and H. M. Hastings, editors, Advances in cognitive science: Steps towards convergence, pages 190–209. Westview Press, Boulder, 1988. † ga:Kampfner88. [288] Y. Maeda and Y. Kanata. A genetic algorithm for an unsupervised learning of neural networks. Eng. Technol. (Japan), 10(2):1–7, 1992. (in Japanese) †CCA 42913/93 ga:Kanata92a. [289] Hiroaki Kitano. Empirical studies on the speed of convergence of neural network training using genetic algorithms. In Proceedings AAAI-90 Eighth National Conference on Artificial Intelligence, volume 2, pages 789–795. AAAI Press/ The MIT Press: Menlo Park, 29. July 3. August 1990. ga:Kitano90a. [290] Hiroaki Kitano. Designing neural networks using genetic algorithms with graph generation system. Complex Systems, 4(4):461–476, 1990. ga:Kitano90b. [291] Hiroaki Kitano. Empirical studies on the utility of genetic algorithms for training and designing of neural networks. Technical Report No. CMU-CMT-92-134, Carnegie-Mellon University, Center for Machine Translation, Pittsburgh,PA, 1990. † ga:Kitano90c. 76 Genetic algorithms and neural networks [292] Michael L. Gargano and Lawrence von Kleeck. Neural Networks and Genetic Algorithms – Business Applications and Case Studies. International Thomson Publishing, London, 1993. †Thomson ga:Kleeck93book. [293] Casimir C. Klimasauskas. Genetic function optimization for time series prediction. Advanced Technology for Developers, 1(3):?, July 1992. †Advanced ... index ga:Klimasauskas92a. [294] Casimir C. Klimasauskas. Hybrid neuro-genetic approach to trading algorithms. Advanced Technology for Developers, 1(7):1–8, November 1992. ga:Klimasauskas92b. [295] Casimir C. Klimasauskas. Neural networks: An engineering perspective. IEEE Communications Magazine, 30(9):50–53, September 1992. ga:Klimasauskas92d. [296] M. Kouchi, H. Inayoshi, and T. Hoshino. Optimization of neural-net structure by genetic algorithm with diploidy and geographical isolation model. Journal of Japanese Society for Artificial Intelligence, 7(3):509– 517, 1992. (in Japanese) * CCA 6912/93 ga:Kouchi92. [297] John R. Koza and James P. Rice. Genetic generation of both the weights and architecture for a neural network. In Proceedings of International Joint Conference on Neural Networks, volume II, pages 397–404, Seattle, WA, 8.-12. July 1991. IEEE Press. * ga:Koza91g. [298] Deborah A. Stacey and Stefan Kremer. The Guelph Darwin project: The evolution of neural networks by genetic algorithms. In 1991 International Joint Conference on Neural Networks - IJCNN 91, volume II, pages A–957, Seattle, WA, 8.-14. July 1991. IEEE, New York. ga:Kremer91a. [299] I. Kupfermann, D. Deodhar, S. R. Rosen, and K. R. Weiss. The use of genetic algorithms to explore neural mechanisms that optimize rhythmic behaviors - quasi-realistic models of feeding behavior in Aplysia. In F. H. Eeckman and J. M. Bower, editors, Computation and Neural Systems, pages 295–300, San Francisco, CA, 26.-29. July 1993. Kluwer Academic Publishers, Norwell. †P61025/94 ga:KRWeiss93a. [300] L. Kiernan and Kevin Warwick. Adaptive alarm processor for fault diagnosis on power transmission networks. Intelligent Systems Engineering, 2(1):25–37, 1993. * ga:KWarwick93b. [301] W. K. Lai and G. G. Coghill. Genetic breeding of control parameters for the Hopfield/Tank neural net. In Proceedings of the IJCNN International Joint Conference on Neural Networks, volume IV, pages 618–623, Baltimore, MD, 7.-11. June 1992. IEEE, New York. ga:Lai92. [302] Ronald W. Larsen and Jeffrey S. Herman. A comparison of evolutionary programming to neural networks and an application of evolutionary programming to a navy mission planning problem. In Fogel and Atmar [1890], pages 127–133. †[6] ga:Larsen92a. [303] Gunar E. Liepins. Comparison of neural classifier system approaches to the multiplexer problem. Neural Networks, 1(1):196, 1988. (Proceedings of International Neural Network Society 1988 First Annual Meeting, Boston, MA, 6.-10. Sep.) * EEA 125457/89 ga:Liepins88c. [304] Eric I. Chang, Richard P. Lippmann, and David W. Tong. Using genetic algorithms to select and create features for pattern classification. In 1990 International Joint Conference on Neural Networks - IJCNN 90, volume 3, pages 747–752, San Diego, CA, 17.-21. June 1990. IEEE, New York. ga:Lippmann90a. [305] Lae-Jeong Park and Cheol Hoon Park. Fast layer-by-layer training of the feedforward neural network classifier with genetic algorithm. In IJCNN’93 [276], pages 2595–2598. ga:LJPark93a. [306] Leah Lucille Rogers. Optimal groundwater remediation using artificial neural networks and the genetic algorithm. PhD thesis, Stanford University, 1992. * DAI 53/9 ga:LLRogersThesis. [307] Reinhard Lohmann. ga:Lohmann92b. Structure evolution in neural systems. pages 395–411, 1992. †Back/bib/unp [308] Peter J. B. Hancock and L. S. Smith. Gannet: Genetic design of a neural net for face recognition. In Schwefel and Männer [1896], pages 292–296. † ga:LSSmith90. [309] A. P. de Weijer, Carlos B. Lucasius, Lutgarde M. C. Buydens, Gerrit Kateman, and H. M. Heuvel. Using genetic algorithms for an artificial neural network model inversion. Chemometrics and Intelligent Laboratory Systems, 20(1):45–55, August 1993. * CCA 68453/93 ga:Lucasius93f. [310] Mark A. Beaumont. Evolution of optimal behaviour in networks of Boolean automata. Journal of Theoretical Biology, 165(4):455–476, 21. December 1993. ga:MABeaumont93a. [311] Nigel Dodd, Donald Macfarlane, and C. Marland. Optimization of artificial neural network structure using genetic techniques on multiple transputers. In P. Welch, D. Stiles, T. L. Kunii, and A. Bakkers, editors, Transputing ’91. Proceedings of the World Transputer User Group (WOTUG), pages 687–700, Sunnyvale, CA, 22.-26. April 1991. IOS Press, Amsterdam. †ACM/91 ga:Macfarlane91a. Bibliography 77 [312] Hideyuki Takagi and Michael A. Lee. Neural networks and genetic algorithm approaches to auto-design of fuzzy systems. In ?, editor, Proceedings of the International Conference on Fuzzy Logic in Artificial Intelligence, page ?, Linz (Austria), 28. - 30. June 1993. ? † ga:MALee93c. [313] M. Anthony Lewis, Andrew H. Fagg, and Alan Solidum. Genetic programming approach to the construction of a neural network for control of a walking robot. In Proceedings of the 1992 IEEE International Conference on Robotics and Automation, volume 3, pages 2618–2623, Nice (France), 12.-14. May 1992. IEEE Computer Society Press, Los Alamitos, CA. * CCA 26693 EI 063875/93 ga:MALewis92a. [314] Martin Mandischer. Representation and evolution of neural networks. In Albrecht et al. [1889], pages 643–649. ga:Mandischer93a. [315] Martin Mandischer. Genetic optimization and representation of neural networks. In Proceedings of the Fourth Australian Conference on Neural Networks (ACNN’93), pages 122–125, Melbourne (Australia), 1.-3. February 1993. Sydney University, Electrical Engineering. †CCA 941/94 ga:Mandischer93b. [316] Martin Mandischer. Genetische Algorithmen zur Optimierung Konnektionistischer Modelle. Master’s thesis, University of Dortmund, Department of Computer Science, 1992. † ga:MandischerMSThesis. [317] M. Mangel. Evolutionary optimization and neural network models of behaviour. Journal of Mathematical Biology, 28(3):237–256, 1990. †Fogel/bib ga:Mangel90a. [318] Vittorio Maniezzo. Searching among search spaces: hastening the genetic evolution of feedforward neural networks. In Albrecht et al. [1889], pages 635–642. ga:Maniezzo93a. [319] Vittorio Maniezzo. Anna Eleonora: Genetic evolution of feedforward neural networks. Technical Report Technical Report No. 93-003, Politecnico di Milano, Dipartimento di Elettronica, 1993. † ga:Maniezzo93b. [320] Sergio Margarita. Neural networks, genetic algorithms and stock trading. In Teuvo Kohonen, Kai Mäkisara, Olli Simula, and Jari Kangas, editors, Artificial Neural Networks, Proceedings of the 1991 International Conference on Artificial Neural Networks (ICANN-91), volume 2, pages 1763–1766, Espoo (Finland), 24.-28. June 1991. North-Holland. ga:Margarita91. [321] Sergio Margarita. Genetic neural networks for financial markets: Some results. In Bernd Neumann, editor, ECAI 92 10th European Conference on Artificial Intelligence, pages 211–213, Vienna (Austria), 3.-7. August 1992. John Wiley & Sons. * CCA 68032/93 ga:Margarita92. [322] Borut Maric̈ić and Z. Nikolov. Gennet-system for computer aided neural network design using genetic algorithms. In Maureen Caudill, editor, Proceedings of the International Conference on Neural Networks (IJCANN-90-WASH-DC), volume 1, pages A102–A105, Washington, DC, 15.-19. Jan. 1990. Lawrence Erlbaum Associates. †P48154 ga:Maricic90. [323] Borut Maric̈ić. Dynamic versus genetic versus chaotic programming. chapter 19, pages 501–533. 1992. †[6] ga:Maricic92a. [324] S. J. Marshall and R. F. Harrison. Optimization and training of feedforward neural networks by genetic algorithms. In Second International Conference on Artificial Neural Networks, volume IEE Conference Publications No. 349, pages 39–43, London (UK), 18.-20. November 1991. IEE, London. ga:Marshall91. [325] Leonardo Martı́. Genetically generated neural networks I: Representational effects. In Proceedings of the IJCNN International Joint Conference on Neural Networks, volume IV, pages 537–542, Baltimore, MD, 7.-11. June 1992. IEEE, New York. ga:Marti92a. [326] Leonardo Martı́. Genetically generated neural networks II: Searching for an optimal representation. In Proceedings of the IJCNN International Joint Conference on Neural Networks, volume II, pages 221–226, Baltimore, MD, 7. -11. June 1992. IEEE, New York. ga:Marti92b. [327] Timothy Masters. Practical neural network recipes in C++, chapter 8, Genetic Optimization. Academic Press, Inc., San Diego, CA, 1993. †Computing Reviews Apr. 94 ga:Masters93book. [328] Alastair D. McAulay and Jae Chan Oh. Image learning classifier system using genetic algorithms. In Proceedings of the IEEE 1989 National Aerospace and Electronics Conference (NAECON 1989), pages 705–713, Dayton, OH, 22.-26. May 1989. IEEE, New York. ga:McAulay89. [329] S. R. Jockusch and J. S. McCaskill. Evolutionary construction algorithms for topology conserving neural nets. In I. Aleksander and J. Taylor, editors, Artificial Neural Networks 2, Proceedings of the 1992 International Conference on Artificial Neural Networks (ICANN-92), volume 2, pages 979–982, Brighton, England, 4.-7. September 1992. Elsevier Science Publ. B. V., Amsterdam. ga:McCaskill92a. [330] John R. McDonnell and Don Waagen. Evolving neural network architecture. In Su-Shing Chen, editor, Neural and Stochastic Methods in Image and Signal Processing, volume SPIE-1766, pages 690–701, San Diego, CA, 20. -23. July 1992. The International Society for Optical Engineering. ga:McDonnell92a. 78 Genetic algorithms and neural networks [331] John R. McDonnell and Don Waagen. Determining neural network connectivity using evolutionary programming. In Avtar Singh, editor, Conference record of the Twenty-Sixth Asilomar Conference on Signals, Systems & Computers, volume 2, pages 786–790, Pacific Grove, CA, 26.-28. October 1992. IEEE Computer Society Press, Los Alamitos, CA. ga:McDonnell92b. [332] John R. McDonnell. Training neural networks with weight constraints. In Fogel and Atmar [1890], pages 111–119. †[6] ga:McDonnell92f. [333] John R. McDonnell and Don Waagen. Evolving neural network connectivity. In IEEENN93 [275], pages 863–868. ga:McDonnell93a. [334] John R. McDonnell and Don Waagen. Neural network structure design by evolutionary programming. In David B. Fogel and W. Atmar, editors, Proceedings of the 2nd Annual Conference on Evolutionary Programming, page ?, La Jolla, CA, 25.-26. February 1993. Evolutionary Programming Society, San Diego. ga:McDonnell93b. [335] John R. McDonnell and Don Waagen. Determining neural network hidden layer size using evolutionary programming. In Proceedings of the World Congress on Neural Networks WCNN’93, volume III, pages 564–567, Portland, OR, 11.-15. July 1993. Lawrence Erlbaum Ass., Inc., Hillsdale, NJ. ga:McDonnell93e. [336] John R. McDonnell and Don Waagen. Determining neural network connectivity using evolutionary programming. Goverment report AD-A266853/1, Naval Command, Control and Ocean Surveillance Centre, 1993. * CA 5246 Vol. 38 No. 7/8 ga:McDonnell93f. [337] Dipankar Dasgupta and Douglas R. McGregor. Designing neural networks using the structured genetic algorithm. In I. Aleksander and J. Taylor, editors, Artificial Neural Networks 2, Proceedings of the 1992 International Conference on Artificial Neural Networks (ICANN-92), volume 1, pages 263–268, Brighton, England, 4.-7. September 1992. Elsevier Science Publ. B. V., Amsterdam. ga:McGregor92c. [338] Dipankar Dasgupta and Douglas R. McGregor. Designing application-specific neural networks using the structured genetic algorithm. In Schaffer and Whitley [125], pages 87–96. also as [339] ga:McGregor92f. [339] Dipankar Dasgupta and Douglas R. McGregor. Designing application-specific neural networks using the structured genetic algorithm. Technical Report IKBS-9-92, University of Strathclyde, Department of Computer Science, Galsgow, 1993. (also as [338]; ftp://reports-ftp.cs.strath.ac.uk/researchreports/ ikbs-9-92.ps.Z) ga:McGregor92ff. [340] Dipankar Dasgupta and Douglas R. McGregor. Genetically designing neuro-controllers for a dynamic system. In IJCNN’93 [276], pages 2951–2954. ga:McGregor93a. [341] Dipankar Dasgupta and Douglas R. McGregor. Evolving neurocontrollers for pole balancing. In Stan Gielen and Bert Kappen, editors, ICANN’93 Proceedings of the International Conference on Artificial Neural Networks, pages 834–837, Amsterdam (The Netherlands), 13.-16. September 1993. Springer-Verlag, Berlin. ga:McGregor93b. [342] Filippo Menczer and Domenico Parisi. “sexual” reproduction in neural networks. Technical Report PCIA Technical Report, Institute of Psychology CNR, Rome, 1990. †Menczer92a ga:Menczer90a. [343] Filippo Menczer and Domenico Parisi. Evidence of hyperplanes in the genetic learning of neural networks. Biological Cybernetics, 66(3):283–289, 1992. ga:Menczer92a. [344] Filippo Menczer and Domenico Parisi. Recombination and unsupervised learning: effects of crossover in the genetic optimization of neural networks. Network: Computation in Neural Systems, 3(4):423–442, 1992. * CCA 37264/93 ga:Menczer92b. [345] C. N. Schizas, C. S. Pattichis, and L. T. Middleton. Neural networks, genetic algorithms and the K-means algorithm: in search of data classification. In Schaffer and Whitley [125], pages 201–222. * EEA 70672/93 ga:Middleton92a. [346] Brad Fullmer and Risto Miikkulainen. Using marker-based genetic encoding of neural networks to evolve finite-state behaviour. In Varela and Bourgine [1897], pages 255–262. (ftp://cs.utexas.edu/pub/ neural-nets/papers/fullmer.genetic-encoding.ps.Z) ga:Miikkulainen92a. [347] David E. Moriarty and Risto Miikkulainen. Evolving complex Othello strategies using marker-based genetic encoding of neural networks. Technical Report AI93-206, The University of Texas at Austin, Department of Computer Science, September 1993. (ftp://cs.utexas.edu/pub/neural-nets/papers/ moriarty.othello.ps.Z) ga:Miikkulainen93a. [348] Michael McInerney and Atam P. Dhawan. Use of genetic algorithms with back propagation in training of feed-forward neural networks. In IEEENN93 [275], pages 203–208. ga:MMcInerney93a. Bibliography 79 [349] E. Monte, D. Hidalgo, J. Mariño, and I. Hernáez. A vector quantization algorithm based on genetic algorithms and LVQ. In ?, editor, Proceedings of the NATO-ASI Bubión, pages 231–, ?, ? 1993. ? †[1021] ga:Monte93a. [350] Heinz Mühlenbein. Parallel genetic algorithms and neural networks as learning machines. In D. J. Evans, G. R. Joubert, and H. Liddell, editors, Proceedings of the International Conference Parallel Computing ’91, pages 91–103, London, 3.-6. September 1991. North-Holland, Amsterdam. †Fogel/bib ga:Muhlenbein91f. [351] Byoung-Tak Zhang and Heinz Mühlenbein. Genetic programming of minimal neural nets using Occam’s razor. In Forrest [1901], pages 342–349. ga:Muhlenbein93b. [352] Byoung-Tak Zhang and Heinz Mühlenbein. Evolving optimal neural networks using genetic algorithms with Occam’s razor. Complex Systems, 7(3):199–220, June 1993. * CCA 66251/94 ga:Muhlenbein93e. [353] Paul W. Munro. Genetic search for optimal representations in neural networks. In Albrecht et al. [1889], pages 628–634. ga:Munro93a. [354] Marco Muselli and Sandro Ridella. Global optimization of functions with the interval genetic algorithm. Complex Systems, 6(3):193–212, June 1992. ga:Muselli92. [355] Tomoharu Nagao, Takeshi Agui, and Hiroshi Nagahashi. Structural evolution of neural networks by a genetic method. Transactions of the Institute of Electronics, Information, and Communication Engineers D-II (Japan), J75D-II(9):1634–1637, 1992. (in Japanese) * CCA 6954/93 ga:Nagao92b. [356] Tomoharu Nagao, Takeshi Agui, and Hiroshi Nagahashi. Structural evolution of neural networks by a genetic method. Transactions of the Institute of Electronics, Information, and Communication Engineers D-II (Japan), J76D-II(3):557–565, 1993. (in Japanese) * CCA 47997/93 ga:Nagao93a. [357] Tomoharu Nagao, Takeshi Agui, and Hiroshi Nagahashi. Structural evolution of neural networks having arbitrary connection by a genetic method. IEICE Transactions on Information and Systems, E76-D(6):689– 697, June 1993. ga:Nagao93b. [358] Tomoharu Nagao, Takeshi Agui, and Hiroshi Nagahashi. A genetic method for optimization of asynchronous random neural networks and its application to action control. In IJCNN’93 [276], pages 1893– 1896. ga:Nagao93c. [359] Hirotaka Nakayama, Tadashi Iwata, and Toshiyuki Yamauchi. Learning and structuring of neural networks using genetic algorithm and linear programming. In IJCNN’93 [276], pages 2702–2705. ga:Nakayama93a. [360] S. C. Ng, Shu H. Leung, and Andrew Luk. Improving the convergence of back-propagation using genetic search. In ?, editor, Proceedings of the 1993 IEEE International Workshop on Intelligent Signal Processing and Communications Systems (ISPACS’93), page ?, Tohoku University, Sendai (Japan), 27.-29. October 1993. IEEE Communications Society. †program ga:Ng93a. [361] A. W. O’Neill. Genetic based training of two-layer, optoelectronic neural network. Electronics Letters, 28(1):47–48, January 1992. ga:O’Neill92a. [362] S. Oliker, M. Furst, and O. Maimon. A distributed genetic algorithm for neural network design and training. Complex Systems, 6(5):459–477, 1992. †CCA 42891/93 ga:Oliker92a. [363] S. Oliker, M. Furst, and O. Maimon. Design architectures and training of neural networks with a distributed genetic algorithm. In IEEENN93 [275], pages 199–202. ga:Oliker93a. [364] G. Deon Oosthuizen. Machine learning: A mathematical framework for neural network, symbolic and genetics-based learning. In Schaffer [1894], pages 385–390. ga:Oosthuizen89. [365] Tomasz Ostrowski. Adaptive filters design using genetic algorithm. In ?, editor, Laser Technology IV, volume SPIE-2202, pages 590–594, Szczecin-Swinoujscie (Poland), 26. -30. September 1993. The International Society for Optical Engineering, Bellingham, WA. * A95-26130 ga:Ostrowski93a. [366] P. M. Palagi and L. A. V. Decarvalho. Neural networks learning with genetic algorithms. In R. Trappl, editor, Cybernetics and Systems Research 92, Proceedings of the 11th European Meeting on Cybernetics and System Research, volume 2, pages 1405–1414, Vienna (Austria), 21. -24. April 1992. World Scientific Publishing Company, Pte., Ltd., Singapore. †P54144 ga:Palagi92. [367] Jan Paredis. The evolution of behaviour: Some experiments. In Meyer and Wilson [1900], pages 419–426. ga:Paredis91a. [368] Domenico Parisi, Stefano Nolfi, and Federico Cecconi. Learning, behavior, and evolution. In Varela and Bourgine [1897], pages 207–216. ga:Parisi91a. [369] Federico Cecconi and Domenico Parisi. Evolving organisms that can reach for objects. In Meyer and Wilson [1900], pages 391–399. ga:Parisi91b. 80 Genetic algorithms and neural networks [370] Orazio Miglino, Roberto Pedone, and Domenico Parisi. A “noise gene” for Econets. In Albrecht et al. [1889], pages 588–594. ga:Parisi93a. [371] Stefano Nolfi and Domenico Parisi. Auto-teaching: networks that develop their own teaching input. In ? [1898], pages 845–862. ga:Parisi93b. [372] M. Srinivas and L. M. Patnaik. Learning neural network weights using genetic algorithms improving performance by search-space reduction. In 1991 IEEE International Joint Conference on Neural Networks (IJCANN91), volume 3, pages 2331–2336, Singapore, 18.-21. November 1991. IEEE, New York. * P52389 EI A099218/92 ga:Patnaik91a. [373] J. J. Merelo, A. Paton, A. Canas, A. Prieto, and F. Moran. Genetic optimization of a multilayer NN for cluster classification tasks. Neural Network World, ?(2):175–186, 1993. †News ga:Paton93a. [374] J. J. Merelo, A. Paton, A. Canas, A. Prieto, and F. Moran. Optimization of a competitive learning neural network by genetic algorithms. In Proceedings of the International Workshop on Artificial Neural Networks (IWANN’93), pages 185–192, Sitges (Spain), 9.-11. June 1993. Springer-Verlag, Berlin. * CCA 17308/93 ga:Paton93b. [375] Charles C. Peck, Atam P. Dhawan, and Claudia M. Meyer. Genetic algorithm based input selection for a neural network function approximator with applications to SSME health monitoring. NASA Contract Final Report NASA-CR-199089, Sverdrup Technology, Inc., Brook Park, OH, 1991. †N95-32768 ga:Peck91a. [376] Charles C. Peck, Atam P. Dhawan, and Claudia M. Meyer. Genetic algorithm based input selection for a neural network function approximator with applications to SSME monitoring. In IEEENN93 [275], pages 1115–1122. ga:Peck93a. [377] H. Bruce Penfold, O. F. Diessel, and M. W. Bentink. A genetic breeding algorithm which exhibits selforganizing in neural networks. In M. H. Hamza, editor, Artificial Intelligence Application & Neural Networks (AINN’90), pages 293–296, Zürich, 25.-27. June 1990. ACTA Press, Anaheim, CA. ga:Penfold90. [378] H. Bruce Penfold, Uwe Kohlmorgen, and Heinrich Schmeck. Deriving application-specific neural nets with a massively parallel genetic algorithm. Report 267, University of Karlsruhe, Institut für angewandte Informatik und formale Beschreibungverfahren, 1993. †Branke ga:Penfold93a. [379] Johanna Persson. Genetic algorithms and neural networks for optimization of hydro power production. Master’s thesis, Lund Institute of Technology, Department of Industrial Electrical Engineering and Automation, 1993. †Lund /report on activities ga:Persson93a. [380] V. Petridis, Spyros A. Kazarlis, A. Papaikonomou, and A. Filelis. A hybrid genetic algorithm for training neural networks. In I. Aleksander and J. Taylor, editors, Artificial Neural Networks 2, Proceedings of the 1992 International Conference on Artificial Neural Networks (ICANN-92), volume 2, pages 953–956, Brighton, England, 4.-7. September 1992. Elsevier Science Publ. B. V., Amsterdam. ga:Petridis92a. [381] V. Petridis, Spyros A. Kazarlis, and A. Papaikonomou. A genetic algorithm for training recurrent neural networks. In IJCNN’93 [276], pages 2706–2709. ga:Petridis93a. [382] Roger S. Gaborski, Peter G. Anderson, David G. Tilley, and Christopher T. Asbury. Genetic algorithm selection of features for hand-printed character identification. In Albrecht et al. [1889], pages 417–422. ga:PGAnderson93a. [383] W. J. M. Philipsen and L. J. M. Cluitmans. Using a genetic algorithm to tune Potts neural networks. In Albrecht et al. [1889], pages 650–657. ga:Philipsen93a. [384] E. E. Pichler, J. D. Keeler, and J. Ross. Comparison of self-organization and optimization in evolution and neural networks models. Complex Systems, 4(?):75–106, 1990. † ga:Pichler90. [385] Gilbert Pitney, Terence R. Smith, and Daniel Greenwood. Genetic design of processing elements for path planning networks. In 1990 International Joint Conference on Neural Networks - IJCNN 90, volume 3, pages 925–932, San Diego, CA, 17.-21. June 1990. IEEE, New York. * EI A089806/91 ga:Pitney90. [386] P. M. Gibson and J. A. Byrne. Neurogen, music composition using genetic algorithms and cooperating neural networks. In Proceedings of the Second International Conference on Artificial Neural Networks, volume Conf. Pub. No. 349, pages 309–313, London (UK), 18.-20. November 1991. IEE. * EI A098639/92 ga:PMGibson91a. [387] Daniel Polani and Thomas Uthmann. Adaptation of Kohonen feature map topologies by genetic algorithms. In Männer and Manderick [1891], pages 421–430. † ga:Polani92a. [388] Daniel Polani and Thomas Uthmann. Training Kohonen feature maps in different topologies: an analysis using genetic algorithms. In Forrest [1901], pages 326–333. ga:Polani93a. Bibliography 81 [389] Jordan B. Pollack. High-level connectionist models. Final report OSURF-760388, Ohio State University, Research Foundation, 1993. * N94-25030 ga:Pollack93c. [390] Vincent W. Porto. Evolutionary methods for training neural networks for underwater pattern classification. In Ray R. Chen, editor, Proceedings of the Twenty-Fourth Asilomar Conference on Signals, Systems & Computers, volume 2, pages 1015–1019, Pacific Grove, California, 5.-7. November 1990. The Computer Society of IEEE/Maple Press. ga:Porto90. [391] Vincent W. Porto. Alternative methods for training neural networks. In Fogel and Atmar [1890], pages 100–110. †Back/bib/unp ga:Porto92a. [392] D. L. Prados. New learning algorithm for training multilayered neural networks that uses genetic algorithm techniques. Electronics Letters, 28(16):1560–1561, 30. July 1992. ga:Prados92a. [393] Nicholas J. Radcliffe. Genetic neural networks on MIMD computers. PhD thesis, University of Edinburgh, Theoretical Physics, 1990. ga:RadciffeThesis. [394] Nicholas J. Radcliffe. Genetic set recombination and its application to neural network topology optimization. Technical Report TR-91-21, Edinburgh Parallel Computing Centre, 1991. (also as [395]; ftp://ftp.epcc.ed.ac.uk/pub/tr/91/tr9121.ps.Z) ga:Radcliffe91b. [395] Nicholas J. Radcliffe. Genetic set recombination and its application to neural network topology optimization. Neural Computing and Applications, 1(1):67–90, 1993. (also as [394]; ftp://ftp.epcc.ed.ac.uk/ pub/tr/91/tr9121.ps.Z) ga:Radcliffe93a. [396] Aaron L. Ranson, Aurali B. Franco, and Margarita G. Chavez. Genetic algorithm like learning rule for neural networks. In 1993, International Conference on Systems, Man and Cybernetics, volume 4, pages 137–142, Le Touquet (France), 17.-20. October 1993. IEEE, New York. ga:Ranson93a. [397] Colin R. Reeves and Nigel C. Steele. A genetic algorithm approach to designing neural network architecture. In D. J. G. James, editor, Proceedings of the 8th International Conference on Systems Engineering, pages 166–173, Coventry (UK), 10.-12. September 1991. Coventry University, Control Theory and Application Centre. † ga:Reeves91a. [398] Colin R. Reeves and Nigel C. Steele. Genetic algorithms and the design of artificial neural networks. IEEE Computer Society Technical Committee on Microprogramming and Microarchitecture, 6(1):15–20, 1991. †ACM/91 ga:Reeves91d. [399] Colin R. Reeves and Nigel C. Steele. Problem-solving by simulated genetic processes: a review and application to neural networks. In Proceedings of the 10th IASTED Symposium on Applied Informatics, pages 269–272, Innsbruck, Austria, 10.-12. February 1992. ACTA Press, Anaheim, CA. † ga:Reeves92b. [400] Colin R. Reeves and Nigel C. Steele. Application of genetic algorithms in artificial neural networks. Systems Science (Poland), 19(4):63–76, 1993. ga:Reeves93f. [401] Robert Hong. Neurocontrols and vision for Mars robots. Advanced Technology for Developers, 1(2):1–, June 1992. †Advanced ... index ga:RHong92a. [402] Louis A. Tamburino and Mateen M. Rizki. Applications of hybrid learning to automated system design. In Proceedings of the AI, Simulation and Planning in High Autonomous Systems Conference 1990, pages 176–183, Tuczon, AZ, 26.-27. March 1990. IEEE, Piscataway, NJ. * www /IEEE ga:Rizki90a. [403] Robert L. Harvey. Genetic algorithm technique for designing neural networks, 1993. (U. S. patent no. 5,249,259. Issued September 28 1993) ga:RLHarvey93a. [404] Philip Robbins, Alan Soper, and Keith Rennolls. Use of genetic algorithms for optimal topology determination in back propagation neural networks. In Albrecht et al. [1889], pages 726–730. ga:Robbins93a. [405] Steve G. Romaniuk. Evolutionary growth perceptrons. In Forrest [1901], pages 334–341. ga:Romaniuk93a. [406] Steve G. Romaniuk. Towards minimal network architectures with evolutionary growth. In IJCNN’93 [276], pages 717–720. ga:Romaniuk93b. [407] Steve G. Romaniuk. Evolutionary growth perceptrons. Technical Report TR67-93, National University of Singapore, 1993. (ftp://ftp.nus.sg/pub/NUS/ISCS/techreports/1993/TRG7-93.ps.gz) ga:Romaniuk93c. [408] R. Reed and II R. J. Marks. Genetic algorithms and neural networks: An introduction. In ?, editor, Northcon/92, Conference Record, pages 293–301, Seattle, WA, 19.-21. October 1992. Electron. Conventions Manage., Ventura, CA. * CCA 39083/94 ga:RReed92a. [409] Stuart H. Rubin. Gmm-pam. a genetic multilevel multicategory perceptron associative memory. In Cooperation 1990 ACM 18th Annual Computer Science Proceedings, pages 366–372, Washington, DC, 20.22. February 1990. ACM, New York. * EI A139234/90 ga:Rubin90a. 82 Genetic algorithms and neural networks [410] William Michael Rudnick. A bibliography of the intersection of genetic search and artificial neural networks. Technical Report CS/E 90-001, Oregon Graduate Center, Department of Computer Science and Engineering, Beaverton, 1990. ga:Rudnick90a. [411] William Michael Rudnick. Evolutionary network design & the contiguity problem. In Proceedings of the World Congress on Neural Networks WCNN’93, volume IV, pages 135–138, Portland, OR, 11.-15. July 1993. Lawrence Erlbaum Ass., Inc., Hillsdale, NJ. ga:Rudnick93a. [412] William Michael Rudnick. Genetic algorithms and fitness variance with an application to the automated design of artificial neural networks. PhD thesis, Oregon Graduate Institute of Science and Technology, Beaverton, 1992. * DAI 53/3 ga:RudnickThesis. [413] Wolfram Schiffmann, M. Joost, and R. Werner. Application of genetic algorithms to the contruction of topologies for multi-layer perceptrons. In Albrecht et al. [1889], pages 675–682. ga:RWerner93a. [414] Tariq Samad. Neural networks – a brief overview. In Proceedings of the American Power Conference, volume 2, pages 1191–1195, Chicago, IL, April 29.-1. May 1990. Illinois Institute of Technology, Chicago, IL. * EI A096807/91 ga:Samad91a. [415] F. J. Vico and F. Sandoval. Use of genetic algorithms in neural networks definition. In A. Prieto, editor, Artificial Neural Networks. International Workshop IWANN’91 Proceedings, pages 196–203, Granada (Spain), 17.-19. September 1990. Springer-Verlag, Berlin. * CCA 62957/92 ga:Sandoval91. [416] Francisco Javier Marin and F. Sandoval. Genetic synthesis of discrete-time recurrent neural network. In Proceedings of the International Workshop on Artificial Neural Networks (IWANN’93), pages 179–184, Sitges (Spain), 9.-11. June 1993. Springer-Verlag, Berlin. ga:Sandoval93a. [417] Chiharu Sano. Hybrid of (ID3 extension + backpropagation) hybrid & (case-based reasoner + Grossberg net) hybrid with economics modeling controlled by genetic algorithm. In Gautam Biswas, editor, Applications of Artificial Intelligence X: Knowledge-Based Systems, volume SPIE-1707, pages 180–194, Orlando, FL, 22. - 24. April 1992. The International Society for Optical Engineering. ga:Sano92. [418] M. N. Narayanan and S. B. Lucas. A genetic algorithm to improve a neural network to predict a patiens response to Warfarin. Methods of Information in Medicine, 32(1):55–58, February 1993. * MEDLINE CCA 35734/93 ga:SBLucas93a. [419] J. David Schaffer, Richard A. Caruana, and Larry J. Eshelman. Using genetic search to exploit the emergent behavior of neural networks. pages 244–248, 1990. † ga:Schaffer90b. [420] J. David Schaffer, Darrell Whitley, and Larry J. Eshelman. Combinations of genetic algorithms and neural networks: A survey of the state of the art. In Schaffer and Whitley [125], pages 1–37. † ga:Schaffer92a. [421] Wolfram Schiffmann. Selbstorganisation neuronaler Netze nach der Prinzipien der Evolution. Bericht Nr. 7, University of Koblenz, Institute of Physics, 1989. † ga:Schiffmann89a. [422] Wolfram Schiffmann and Klaus Mecklenburg. Genetic generation of backprogation trained neural networks. In Eckmiller et al. [170], chapter 5: Self-Organization and Learning in Neural Networks, pages 205–208. ga:Schiffmann90a. [423] Wolfram Schiffmann, M. Joost, and R. Werner. Performance evaluation of evolutionarily created neural network topologies. In Schwefel and Männer [1896], pages 274–283. † ga:Schiffmann90b. [424] Marc Schoenauer, Edmund Ronald, and S. Damour. Evolving nets for control. In ?, editor, Actes du Gongrés Neuro-Nimes, pages 271–278, Nimes (France), 25.-29. October 1993. EC2, Nanterre (France). * CCA 75873/94 ga:Schoenauer93b. [425] M. Scholz. A learning-strategy for neural networks based on a modified evolutionary strategy. In Schwefel and Männer [1896], pages 314–319. † ga:Scholz90. [426] Bart Selman and Graeme Hirst. Parsing as an energy minimization problem. In Davis [1902], pages 141–154. ga:Selman87. [427] R. Serra. Genetic algorithms and connectionism. In C. Frediani, editor, Italian Physical Society Conference Proceedings, volume 31, pages 287–292, Marciana Marina, Italy, 12.-18. May 1990 1991. Editrice Compositori, Bologna. †P49915 ga:Serra91. [428] N. Shamir, D. Saad, and E. Marom. Using the functional behavior of neurons for genetic recombination in neural nets training. Complex Systems, 7(6):445–467, December 1993. * CCA 36666/95 ga:Shamir93a. [429] Ronald Shonkwiler and K. R. Miller. Genetic algorithm/neural network synergy for nonlinearly constrained optimization problems. In Schaffer and Whitley [125], pages 248–257. * CCA 58173/93 ga:Shonkwiler92a. Bibliography 83 [430] Sam-Kit Sin and Rui J. P. deFigueiredo. A method for the design of evolutionary multilayer neural networks. In IEEENN93 [275], pages 869–874. ga:Sin93a. [431] Sankar K. Pal, Dinabandhu Bhandari, P. Harish, and Malay K. Kundu. Cellular neural networks, genetic algorithms and object extraction. Far East Journal of Mathematical Sciences, 1(2):139–155, December 1993. ga:SKPal93b. [432] M. Sobotka. Network design - an application of genetic algorithms. In P. D. Rizik, editor, Proceedings of the 1992 Applied Defence Simulation Conference, pages 63–66, Newport Beach, CA, 20.-22. January 1992. Soc. Computer Simulation. †P54967 ga:Sobotka92. [433] William M. Spears. Using neural networks and genetic algorithms as heuristics for NP-complete problems. Master’s thesis, George Mason University, Department of Computer Science, 1989. ga:Spears89a. [434] William M. Spears and Kenneth A. De Jong. Using neural networks and genetic algorithms as heuristics for NP-complete problems. In Maureen Caudill, editor, Proceedings of the International Conference on Neural Networks (IJCANN-90-WASH-DC), volume 1, pages A118–A121, Washington, DC, 15.-19. Jan. 1990. Lawrence Erlbaum Associates. (also AIC Report No. AIC-90-013) ga:Spears90a. [435] William M. Spears and Vic Anand. A study of crossover operators in genetic programming. In Z. W. Ras and M. Zemankova, editors, Methodologies for Intelligent Systems, 6th International Symposium, ISMIS ’91, pages 409–418, Charlotte, N.C., USA, 16. - 19. October 1991. Springer-Verlag. ga:Spears91b. [436] Piet Spiessens and Jan Torreele. Massively parallel evolution of recurrent networks: an approach to temporal processing. In Varela and Bourgine [1897], pages 70–77. ga:Spiessens92a. [437] Joachim Stender and Tom Addis. Symbols versus neurons? chapter Using the genetic algorithm to adapt intelligent systems, page ? IOS Press, Amsterdam, 1990. † ga:Stender90a. [438] R. Keesing and David G. Stork. Evolution and learning in neural networks: The number and distribution on learning trials affect the rate of evolution. In Richard P. Lippmann, J. E. Moody, and D. S. Touretzky, editors, Advances in Neural Information Processing Systems 3. Proceedings of the 1990 Conference (NIPS3), page ?, Denver, CO, 26.-29. November 1990. Morgan Kaufmann, Palo Alto, CA. †[971] ga:Stork90a. [439] David G. Stork, Bernie Jackson, and Scott Walker. “Non-optimality” via pre-adaptation in simple neural systems. In Langton et al. [1895], pages 409–429. ga:Stork92a. [440] David G. Stork. Preadaptation and principles of organization in organisms. In Jay E. Mittenthal and Arthur B. Baskin, editors, The Principles of Organization in Organisms, Proceedings of the Workshop on Principles of Organization in Organisms, volume SFI Studies in the Sciences of Complexity Vol. XIII, pages 205–224, Santa Fe, NM, June 1990 1992. Addison-Wesley Publishing Company, Reading, MA. ga:Stork92b. [441] Laurent Kwiatkowski and Jean-Paul Stromboni. Neuromimetic algorithms processing: Tools for design of dedicated architectures. In Albrecht et al. [1889], pages 706–711. ga:Stromboni93a. [442] Okamoto J. Sugimoto and S. Hosokawa. A learning method in neural network using genetic algorithm. In ?, editor, Proceedings of Kansai-section Joint Convention of Institute of Electrical Engineering, volume G235 G8-8, page ?, ?, ? 1991. ? †[860] ga:Sugimoto91a. [443] Stewart W. Wilson. Peceptron redux: Emergence of structure. pages 249–256, 1990. ga:SWWilson90a. [444] Hideyuki Takagi. Neural networks and genetic algorithm techniques for fuzzy systems. In Proceedings of the World Congress on Neural Networks - WCNN ’93, pages 631–634, Portland, OR, 11.-15. July 1993. IEEE. †conf. prog. ga:Takagi93a. [445] Hideyuki Takagi. Fusion techniques of fuzzy-systems and neural networks, and fuzzy-systems and genetic algorithms. In B. Bosacchi and J. C. Bezdek, editors, Applications of Fuzzy Logic Technology, volume SPIE-2061, pages 402–413, Boston, MA, 8.-10. September 1993. The International Society for Optical Engineering. †P60135 ga:Takagi93b. [446] H. Takahashi, Takeshi Agui, and Hiroshi Nakahashi. Designing adaptive neural-network architectures and their learning parameters using genetic algorithms. In D. W. Ruck, editor, Science of Artificial Neural Networks II, volume SPIE-1966, pages 208–217, Orlando, FL, 13. -16. April 1993. The International Society for Optical Engineering. * P58486/93 CCA 25006/94 ga:TakeshiAgui93a. [447] Astro Teller. Learning mental models. In ?, editor, Proceedings of the Fifth Workshop on Neural Networks: An International Conference on Computational Intelligence: Neural Networks, Fuzzy Systems, Evolutionary Programming, and Virtual Reality, page ?, ?, ? 1993. ? †Langdon/bib ga:Teller93a. [448] Dirk Thierens, Johan Suykens, Joos Vandewalle, and Bart De Moor. Genetic weight optimization of a feedforward neural network controller. In Albrecht et al. [1889], pages 658–663. ga:Thierens93a. 84 Genetic algorithms and neural networks [449] T. Morimoto, T. Tekeuchi, and Y. Hashimoto. Growth optimization of plant by means of the hybrid system of genetic algorithm and neural network. In IJCNN’93 [276], pages 2979–2982. ga:TMorimoto93a. [450] B. H. V. Topping and A. I. Khan, editors. Neural Networks and Combinatorial Optimization in Civil and Structural Engineering, Edinburgh (UK), 17.-19. August 1993. Civil Comp. Press, Edingburgh. †P58786/94 ga:Topping93book. [451] Jan Torreele. Temporal processing with recurrent networks: An evolutionary approach. In Belew and Booker [1903], pages 555–561. ga:Torreele91. [452] Gábor J. Tóth and András Lörincz. Genetic algorithm with migration on topology conserving maps. In Stan Gielen and Bert Kappen, editors, ICANN’93 Proceedings of the International Conference on Artificial Neural Networks, pages 605–608, Amsterdam (The Netherlands), 13.-16. September 1993. Springer-Verlag, Berlin. ga:Toth93a. [453] Gábor J. Tóth and András Lörincz. Genetic algorithm with migration on topology conserving maps. In Proceedings of the World Congress on Neural Networks WCNN’93, volume III, pages 168–171, Portland, OR, 11.-15. July 1993. Lawrence Erlbaum Ass., Inc., Hillsdale, NJ. ga:Toth93b. [454] David S. Touretzky and Geoffrey E. Hinton. Pattern matching and variable binding in a stochastic neural network. In Davis [1902], pages 155–169. ga:Touretzky87. [455] David S. Touretzky, editor. Advances in Neural Information Processing Systems 2, Proceedings of the Neural Information Processing Systems (NIPS), Denver, CO, 1990. Morgan Kaufmann Publishers. ga:Touretzky90. [456] Takayuki Yamada and Tetsuro Yabuta. Remarks on neural network controller which uses genetic algorithm. In IJCNN’93 [276], pages 2783–2786. ga:TYamada93a. [457] Uwe Hartmann. Computational complexity of neural networks and classifier systems. Diplomarbeit, University of Dortmund, 1992. † ga:UHartmannMSThesis. [458] Byoung-Tak Zhang and Gerd Veenker. Neural networks that teach themselves through genetic discovery of novel examples. In Proceedings of the International Joint Conference on Neural Networks, volume 3, pages 690–695, Singapore, 18.-21. November 1991. IEEE. †EI M008476/93 Fukumi93a ga:Veenker91a. [459] Paul F. M. J. Verschure. Formal minds and biological brains: AI and Edelman’s extended theory of neuronal group selection. IEEE Expert, 8(5):66–75, October 1993. ga:Verschure93a. [460] Kevin W. Whitaker, Ravi K. Prasanth, and Robert E. Markin. Specifying exhaust nozzle contours with a neural network. AIAA Journal, 31(2):273–277, February 1993. ga:Whitaker93a. [461] Darrell Whitley. Applying genetic algorithms to neural net learning. Technical Report CS-88-128, Colorado State University, Department of Computer Science, Fort Collins, 1988. † ga:Whitley88c. [462] Darrell Whitley. Applying genetic algorithms to neural network problems. Neural Networks, 1(1):230, 1988. (Proceedings of International Neural Network Society 1988 First Annual Meeting, Boston, MA, 6.-10. Sep.) * EEA 125471/89 ga:Whitley88d. [463] Darrell Whitley and Thomas Hanson. Optimizing neural networks using faster, more accurate genetic search. In Schaffer [1894], pages 391–396. ga:Whitley89a. [464] Darrell Whitley. The genitor algorithm: Using genetic recombination to optimize neural networks. Technical Report No. CS-89-107, Colorado State University, Department of Computer Science, Fort Collins, 1989. † ga:Whitley89d. [465] Darrell Whitley and Christopher Bogart. The evolution of connectivity: Pruning neural networks using genetic algorithms. Technical Report No. CS-89-113, Colorado State University, Department of Computer Science, Fort Collins, 1989. † ga:Whitley89e. [466] Darrell Whitley and Timothy John Starkweather. Optimizing small neural networks using a distributed genetic algorithm. Technical Report No. CS-89-114, Colorado State University, Department of Computer Science, Fort Collins, 1989. † ga:Whitley89f. [467] Darrell Whitley. Applying genetic algorithms to neural network learning. In A. Cohn, editor, Proceedings of the Seventh Conference of the Society for the Study of Artificial Intelligence and Simulation of Behaviour (AISB89), pages 137–144, Brighton (UK), 18.-21. April 1989. Pitman, London. †Fogel/bib ga:Whitley89g. [468] Darrell Whitley and Thomas Hanson. Using genetic recombination to optimize neural networks. In Proceedings of the IJCNN International Joint Conference on Neural Networks, volume II, page 591, Washington, DC, 18.-22. June 1989. IEEE, New York. * EI A139582/90 ga:Whitley89h. Bibliography 85 [469] Darrell Whitley and Christopher Bogart. The evolution of connectivity: Pruning neural networks using genetic algorithms. In Maureen Caudill, editor, International Joint Conference on Neural Networks, (IJCN90-WASH-DC), volume 1, pages A134–A137, Washington, DC, 15.-19. January 1990. Lawrence Erlbaum Assoc. Publ., Hillsdale, NJ. ga:Whitley90b. [470] Darrell Whitley, Timothy John Starkweather, and Christopher Bogart. Genetic algorithms and neural networks: Optimizing connections and connectivity. Parallel Computing, 14(3):347–361, August 1990. † ga:Whitley90d. [471] Darrell Whitley, Stephen Dominic, and Rajarshi Das. Genetic reinforcement learning with multilayer neural networks. In Belew and Booker [1903], pages 562–569. ga:Whitley91d. [472] Stephen Dominic, Darrell Whitley, and C. W. Anderson. Genetic reinforcement learning for neural networks. In 1991 International Joint Conference on Neural Networks - IJCNN 91, volume II, pages 71–76, Seattle, WA, 8.-14. July 1991. IEEE, New York. †EI A083827/92 ga:Whitley91h. [473] J. David Schaffer, Darrell Whitley, and Larry J. Eshelman. Combinations of genetic algorithms and neural networks: A survey of the state of the art. In Schaffer and Whitley [125], pages 1–37. * CCA 58168/93 ga:Whitley92g. [474] Nachimuthu Karunanithi, Rajarshi Das, and Darrell Whitley. Genetic cascade learning for neural networks. In Schaffer and Whitley [125], pages 134–145. ga:Whitley92i. [475] Darrell Whitley, Stephen Dominic, Rajarshi Das, and C. W. Anderson. Genetic reinforcement learning for neurocontrol problems. Machine Learning, 13(2-3):259–284, 1993. ga:Whitley93d. [476] Alexis P. Wieland. Evolving neural network controllers for unstable systems. In 1991 International Joint Conference on Neural Networks - IJCNN 91, volume II, pages 667–673, Seattle, WA, 8.-14. July 1991. IEEE, New York. ga:Wieland91. [477] Willfried Wienholt. Minimizing the system error in feedforward neural networks with evolution strategy. In Stan Gielen and Bert Kappen, editors, ICANN’93 Proceedings of the International Conference on Artificial Neural Networks, pages 490–493, Amsterdam (The Netherlands), 13.-16. September 1993. Springer-Verlag, Berlin. ga:Wienholt93b. [478] Willfried Wienholt. Optimizing the structure of radial basis function networks by optimizing fuzzy inference systems with evolution strategy. Internal Report IR-INI 93-07, Ruhr-Universität Bochum, Institut für Neuroinformatik, 1993. †Back/bib/unp ga:Wienholt93c. [479] Peter Wilke. Simulation of neural networks and genetic algorithms in a distributed computing environment using neurograph. In Stan Gielen and Bert Kappen, editors, ICANN’93 Proceedings of the International Conference on Artificial Neural Networks, pages 1070–1073, Amsterdam (The Netherlands), 13.-16. September 1993. Springer-Verlag, Berlin. ga:Wilke93a. [480] Peter Wilke. Simulation of neural networks and genetic algorithms in a distributed computing environment using NeuroGraph. In Proceedings of the World Congress on Neural Networks WCNN’93, volume I, pages 269–272, Portland, OR, 11.-15. July 1993. Lawrence Erlbaum Ass., Inc., Hillsdale, NJ. ga:Wilke93b. [481] Y. Xiong. Optimization of transportation network design problems using a cumulative genetic algorithm and neural networks. PhD thesis, University of Washington, WA, 1992. †ACM/93 ga:XiongThesis. [482] Xin Yao. A review of evolutionary artificial neural networks. International Journal of Intelligent Systems, 8(4):539–567, April 1992. ga:XYao92. [483] Xin Yao. Evolutionary artificial neural networks. International Journal of Neural Systems (Singapore), 4(3):203–222, September 1993. ga:XYao93b. [484] A. A. Arkadan, P. Du, M. Sidani, and M. Bouji. Performance prediction of SRM drive systems under normal and fault operating conditions using GA-based ANN method. IEEE Transactions on Magnetics, 36(4):1945–1949, July 2000. ga00aAAArkadan. [485] A. D. Brown and H. C. Card. Cooperative coevolution of neural representations. Int. J. Neural Syst., 10(4):311–320, August 2000. * PubMed11052417 ga00aADBrown. [486] Adolfo González Yunes, Miguel A. Ávila Álvarez, Eduardo Gómez Ramı́rez, Xavier Vilasis Cardona, Oriol Mulet, and Ferran Mazzanti. Redes neuronales para identificación y predicción de series de tiempo. Revista del Centro de Investigación, Universidad La Salle, 4(014):45–65, ? 2000. ga00aAGYunes. [487] A. Hunter and K.-S. Chiu. Genetic algorithm design of neural network and fuzzy logic controllers. Soft Computing, 4(3):186–192, ? 2000. * www /Springer ga00aAHunter. 86 Genetic algorithms and neural networks [488] Ankit Jain and David B. Fogel. Case studies in applying fitness distributions in evolutionary algorithms: I. Simple neural networks and gaussian mutation. In Kevin L. Priddy, Paul E. Keller, and David B. Fogel, editors, Applications and Science of Computational Intelligence III, volume SPIE-4055, pages 168–175, ?, March 2000. The International Society for Optical Engineering. * www/SPIE Web ga00aAJain. [489] A. K. Srinastava, K. K. Shukla, and S. K. Srivastava. Application of genetically trained neural network with mutation to intelligent gas sensor. In Nikhil Pal, Arm K. De, and Jyofirmay Des, editors, Advances in Pattern Recognition and Digital Techniques, Proceedings of the 4th International Conference on, pages 326–330, ?, ? 2000. Narosa Publishing House, New Delhi (India). †kirjakauppa/Sanoma-talo ga00aAKSrinastava. [490] Anantha Sundaram, Prasenjeet Ghost, Venkat Venkatasubramanian, James M. Caruthers, and Daniel T. Daly. Fuel-additives design using hybrid neural networks and evolutionary algorithms. In Michael F. Malone and James A. Trainham, editors, Foundations of Computer-Aided Process Design, Proceedings of the 5th International Conference on Chemical Process Design, volume 96 of AIChE Symposium Series No. 323, pages 478–481, Breckenridge, CO, 19.-24. July 1999 2000. American Institute of Chemical Engineers. ga00aASundaram. [491] Astro Teller and Manuela Veloso. Internal reinforcement in a connectionist genetic programming approach. Artificial Intelligence, 120(2):165–198, July 2000. ga00aATeller. [492] Aimin Wang, Lansun Shen, and Zhongxu Zhao. Color tongue image segmentation using fuzzy Kohonen networks and genetic algorithms. In Nasser M. Nasrabadi and Aggelos K. Katsaggelos, editors, Applications of Artificial Neural Networks in Image Processing V, volume SPIE-3962, pages 182–190, ?, April 2000. The International Society for Optical Engineering. * www/SPIE Web ga00aAWang. [493] Brian Carse and Johan Oreland. A note on learning and evolution in neural networks. pages 66–73, 2000. ga00aBCarse. [494] Benyamin Kusunoputro and Ponix Irwanto. Structure optimization of fuzzy neural networks as an expert system using genetic algorithms. In Kevin L. Priddy, Paul E. Keller, and David B. Fogel, editors, Applications and Science of Computational Intelligence III, volume SPIE-4055, pages 219–225, Orlando. FL, 24.-27. April 2000. The International Society for Optical Engineering. * A01-23367 www/SPIE Web ga00aBKusumoputro. [495] B. Y. Kim and K. S. Park. Automatic sleep stage scoring systems using genetic algorithms and neural network. In J. D. Enderle, editor, Proceedings of the 2000 Annual International Conference of the IEEE Engineering in Medicine and Biological Society, volume 2, pages 849–850, Chigaco, IL, USA, 23.-28.July 2000. IEEE, Piscataway, NJ. * www/IEEE ga00aBYKim. [496] C. E. Henderson, W. D. Potter, R. W. McClendon, and G. Hoogenboom. Predicting aflatoxin contamination in peanuts: a genetic algorithm/neural network approach. Applied Intelligence, 12(3):183–192, MayJune 2000. * www /ACM ga00aCEHenderson ⇒ http://portal.acm.org/citation.cfm?id=590912. [497] C. Hervas, J. A. Algar, and M. Silva. Correction of tempeture variations in kinetic-based determinations by use of pruning computational neural networks in conjunction with genetic algorithms. J. Chem. Inf. Comput. Sci., 40(3):724–731, May-June 2000. * PubMed10850776 ga00aCHervas. [498] C. H. Kung, M. J. Devaney, C. M. Huang, and C. M. Kung. Power source scheduling and adaptive load management via a genetic algorithm embedded neural-network. In Proceedings of the 17th IEEE Instrumentation and Measurement Technology Conference, volume ?, pages 1061–1065, Baltimore, MD, USA, 1.-4.May 2000. IEEE, New York. †P89729 ga00aCHKung. [499] Daniel Guyer and Xiukun Yang. Use of genetic artificial neural networks and spectral imaging for defect detection on cherries. Computers and Electronics in Agriculture, 29(?):179–194, ? 2000. ga00aDanielGuyer. [500] D. Devogelaere and M. Rijckaert. Scalars, a way to improve the multi-objective prediction of the GAdCmethod. In C. H. C. Ribeiro and F. M. G. Franca, editors, Sixth Brazilian Symposium on Neural Networks, 2000. Proceedings, volume ?, pages 56–60, Rio de Janeiro, RJ, Brazil, 22.-25.November 2000. IEEE, Piscataway, NJ. * www/IEEE ga00aDDevogelaere. [501] Hugo de Garis, Andrzej Buller, Thierry Dob, Jean Honlet, Padma Guttikonda, and Derek Decesare. Building multimodule systems with unlimited evolvable capacities from modules with limited evolvable capasities (NECs). In Jason Lohn, Adrian Stoica, Didier Keymeulen, and Silvano Colombano, editors, Proceedings of the Second NASA/DoD Workshop on Evolvanle Hardware, pages 225–234, Palo Alto, CA, 13.-15. July 2000. IEEE Computer Society. ga00adeGaris. [502] D. F. Cook, C. T. Ragsdale, and R. L. Major. Combining a neural network with a genetic algorithm for process parameter optimization. Engineering Applications of Artificial Intelligence, 13(?):391–396, ? 2000. ga00aDFCook. Bibliography 87 [503] Dario Floreano and Joseba Urzelai. Evolutionary robots with on-line self-organization and behavioral fitness. Neural Networks, 13(4-5):431–443, May/June 2000. ga00aDFloreano. [504] Daniel Polani and Risto Miikkulainen. Eugenic neuro-evolution for reinforcement learning. pages 1041– 1046, 2000. ga00aDPolani. [505] Dan Ventura and Subhash Kak. Quantum computing and neural information processing. Information Sciences, 128(3-4):147–148, 1. October 2000. †www /Elsevier ga00aDVentura. [506] E. T. Rolls and S. M. Stringer. On the design of neural networks in the brain by genetic evolution. Prog. Neurobiol., 61(6):557–579, August 2000. * PubMed10775797 ga00aETRolls. [507] F. C. Su and W. L. Wu. Design and testing of a genetic algorithm neurali network in the assessment of gait patterns. Medical Engineering & Physics, 22(1):67–74, January 2000. * PubMed10817950 ga00aFCSu ⇒ http://www.ingentaconnect.com/content/els/13504533/2000/ 00000022/00000001/art00011;jsessionid=1kr58u0ul64qo.alexandra?format=print. [508] Forrest H. Bennett III and Eleanor G. Rieffel. Design of decentralized controllers for self-reconfigurable modular robots using genetic programming. In Jason Lohn, Adrian Stoica, Didier Keymeulen, and Silvano Colombano, editors, Proceedings of the Second NASA/DoD Workshop on Evolvanle Hardware, pages 43–52, Palo Alto, CA, 13.-15. July 2000. IEEE Computer Society. ga00aFHBennett. [509] F. Lopez, D. L. Vilarino, and D. Cabello. Design of multiplayer discrete time cellular neural networks for image processing tasks based on genetic algorithms. In The 2000 IEEE International Symposium on Circuits and Systems. ISCAS Geneva, volume 4, pages 133–136, Geneva, Switzerland, 28.-31.May 2000. IEEE, Piscataway, NJ. * www/IEEE ga00aFLopez. [510] Fabrizio Russo. Image filtering using evolutionary neural fuzzy systems. pages 23–43. 2000. ga00aFRusso. [511] G. Rovithakis, M. Maniadakis, and M. Zervakis. A genetically optimised artificial neural network structure for feature extraction and classification of vascular tissue fluorescence. In V. Cantoni and C. Guerra, editors, Fifth IEEE International Workshop on Computer Architectures of Machine Perception, volume ?, pages 107–111, Padova, Italy, 11.-13.September 2000. IEEE, Piscataway, NJ. * www/IEEE ga00aGRovithakis. [512] Hugo de Garis, Michael Korkin, Padma Guttikonda, and Donald Cooley. Evolving detectors of 2D patterns on a simulated CAM-Brain machine: an evolvable hardware tool for building a 75-million-neuron artificial brain. In Sunny Bains and Leo J. Irakliotis, editors, Critical Technologies for the Future of Computing, volume SPIE-4109, pages 13–18, ?, November 2000. The International Society for Optical Engineering. * www/SPIE Web ga00aHdeGaris. [513] Henrik Jacobsson and Björn Olsson. An evolutionary algorithm for inversion of ANNs. In P. P. Wang, editor, Proceedings of the Third International Workshop on Frontiers in Evolutionary Algorithms (FEA2000), pages 1070–1073, Atlantic City, 27. February-3. March 2000. ? †lop ga00aHJacobsson. [514] H. S. Abdelatyzohdy and R. L. Ewing. Smart system neural networks and genetic algorithms for information fusion. In D. Vanlandeghem, editor, 14th European Simulation Multiconference (ESM 2000), volume ?, pages 134–139, Ghent, Belgium, 23.-26.May 2000. Soc. Computer Simulation, San Diego. †P89828 ga00aHSAbdelatyzohdy. [515] Hui-Dong Jin, Kwong-Sak Leung, and Man-Leung Wong. Designing an expanded SOM for the travelling salesman problem by genetic algorithms. page 1079, 2000. ga00aHui-DongJin. [516] Huiyuan Pan, Guang Xi, and Shangjin Wang. Impeller inverse design by neural networks coupled with genetic algorithms. Journal of Aerospace Power, 15(1):47–50, January 2000. * A00-30435 ga00aHuiyuanPan. [517] I. Ono, M. Takahashi, and N. Ono. Evolving neural networks in environments with delayed rewards by a real-coded GA using the unimodal normal distribution crossover. In Proceedings of the 2000 Congress on Evolutionary Computation, volume 1, pages 659–666, La Jolla, CA, USA, 16.-19.July 2000. IEEE, Piscataway, NJ. * www/IEEE ga00aIOno. [518] Joseph Y. Lo, Walker H. Land, and Clayton T. Morrison. Evolutionary programming technique for reducing complexity of artificial neural networks for beast cancer diagnosis. In Kenneth M. Hanson, editor, Medical Imaging 2000: Image Processing, volume SPIE-3979, pages 153–158, ?, June 2000. The International Society for Optical Engineering. * www/SPIE Web ga00aJYLo. [519] J. Zhou, Y. L. Luo, J. H. Zhang, and X. Cui. A neural-network identifier of synchronous machines trained by object-oriented genetic algorithm and back-propagation. In 2000 Winter Meeting of the IEEE Power Engineering Society, volume 1-4, pages 239–242, Singapore, Singapore, 23.-27.January 2000. IEEE, New York. †P89724 ga00aJZhou. 88 Genetic algorithms and neural networks [520] K. D. Kumar and Y. Miyazawa. Flight control system design using neural networks and genetic algorithms. In ?, editor, 38th Aircraft Symposium, volume ?, page ?, Sendai, Japan, 11.-13. October 2000. Japan Society for Aeronautical and Space Sciences. * ga00aKDKumar. [521] Kim H. Yap and Ling Guan. Adaptive image restoration based on hierarchical neural networks. Optical Engineering, 39(7):1877–1890, July 2000. * www/SPIE Web ga00aKHYap. [522] Katsuhiko Kawahito. Method for optimizing nn synapse combined load, 2000. (JP patent no. 2000357255. Issued December 26 2000) * fi.espacenet.com ga00aKKawahito. [523] Kashif Rashid, Jaime A. Ramı́rez, and Ernest M. Freeman. Hybrid optimization in electromagnetics using sensitivity information from a neuro-fuzzy model. IEEE Transactions on Magentics, 36(4):1061–1065, July 2000. ga00aKRashid. [524] K. Z. Mao, K.-C. Tan, and W. Ser. Probabilistic neural-network structure determination for pattern classification. IEEE Transactions on Neural Networks, 11(4):1009–1016, July 2000. ga00aKZMao. [525] Hod Lipson and Jordan B. Pollack. Automatic design and manufacture of robotic lifeforms. Nature, 406(6799):974–978, 31. August 2000. ga00aLipson. [526] Li Ying, Jiao Licheng, and Bai Bendu. Combining wavelet transform and the evolutionary neural network for radar target recognition. In H. H. Szu, M. Veterli, W. J. Campbell, and J. R. Buss, editors, Wavelet Applications VII, volume SPIE-4056, pages 499–506, San Diego, CA, 26. -28. April 2000. The International Society for Optical Engineering, Bellingham, WA. †P89473/00 ga00aLiYing. [527] L. P. B. Scott, J. Chahine, and J. R. Ruggiero. Prediction of protein structures using a Hopfield network. In Proceedings of the Sixth Brazilian Symposium on Neural Networks, page 284, Rio de Janeiro (Brazil), 22.-25. November 2000. ? * www /IEEE ga00aLPBScott. [528] Liam Yew and Chwee Kim. Automatic freeway incident detection system using artificial neural networks and genetic algorithm, 2000. (WIPO patent no. WO 00/07113. Issued February 10 2000) ga00aLYew. [529] Mitchell A. Potter and Kenneth A. De Jong. Cooperative coevolution: An architecture for evolving coadapted subcomponents. Evolutionary Computation, 8(1):1–29, ? 2000. ga00aMAPotter. [530] Masao Ozaki and Wataru Motokawa. Dental age estimation by two computer methods: fuzzy logic and neural network. Biomedical Soft Computing and Human Sciences, 6(1):13–17, ? 2000. ga00aMasaoOzaki. [531] M. Castellano, G. Mastronardi, and V. Bevilacqua. Pattern-matching in high-energy physics by using neural-network and genetic algorithm. In S. Amari, C. L. Giles, M. Gori, and V. Piuri, editors, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, volume 2, pages 159–166, Como, Italy, 24.-27.July 2000. IEEE Computer Soc., Los Alamitos. †P90178 ga00aMCastellano. [532] M. F. Abbod, D. A. Linkens, A. Browne, and N. Cade. A blackboard software architecture for integrated intelligent control systems. Kybernetes, 29(7-8):999–1015, 2000. * ISI ga00aMFAbbod. [533] Michael Hüsken, Jens E. Gayko, and Bernhard Sendhoff. Optimization for problem classes - neural networks that learn to learn. In Xin Yao and David F. Fogel, editors, Proceedings of the 2000 IEEE Symposium on Combinations of Evolutionary Computation and Neural Networks (ECNN 2000), pages 98–109, San Antonio, TX, ? 2000. IEEE Press, New York, NY. ga00aMichaelHusken. [534] Meng Joo Er, Jun Liao, and Jianya Lin. Fuzzy neural networks-based quality prediction system for sintering process. IEEE Transactions on Fuzzy Systems, 8(3):314–324, June 2000. ga00aMJEr. [535] Michael Korkin, Gary Fehr, and Gregory Jeffery. Evolving hardware on a large scale. In Jason Lohn, Adrian Stoica, Didier Keymeulen, and Silvano Colombano, editors, Proceedings of the Second NASA/DoD Workshop on Evolvanle Hardware, pages 173–181, Palo Alto, CA, 13.-15. July 2000. IEEE Computer Society. ga00aMKorkin. [536] Martin Kreutz, Anja Maria Busse, and Bernhard Sendhoff. Evolution of adaptive nonlinear models. In Soo-Young Lee, editor, Seventh International Conference on Neural Information Processing - Proceedings, volume 2, pages 885–890, Taejon, Korea, November 2000. ? ga00aMKreutz. [537] Michael Uelschen and Martin Lawerenz. Design of axial compressor airfoils with artificial neural networks and genetic algorithms. In Fluids 2000 Conference and Exhibit, Denver, CO, 19.-22. June 2000. AIAA. AIAA Paper 2000-2546 * A00-33880 ga00aMUelschen. [538] N. Baba, N. Inoue, and H. Asakawa. Utilization of neural networks and GAs for constructing reliable decision-support systems to deal stocks. In S. Amari, C. L. Giles, M. Gori, and V. Piuri, editors, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, volume 5, pages 111–116, Como, Italy, 24.-27.July 2000. IEEE Computer Soc., Los Alamitos. †P90182 ga00aNBaba. Bibliography 89 [539] N. Kasabov and G. Iliev. Hybrid system for robust recognition of noisy speech-based on evolving fuzzy neural networks and adaptive filtering. In S. Amari, C. L. Giles, M. Gori, and V. Piuri, editors, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, volume 5, pages 91–96, Como, Italy, 24.-27.July 2000. IEEE Computer Soc., Los Alamitos. †P90182 ga00aNKasabov. [540] P. C. W. Beatty, A. Pohlmann, and T. Dimarki. Shape-only identification of breathing system failure. In Proceedings of the 2nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, volume 2, pages 982–984, Chigago, IL, 23.-26. July 2000. IEEE, Piscataway, NJ. * www /IEEE ga00aPCWBeatty. [541] P. R. Harvey and J. F. Boyce. Phyletic evolution of neural feature detectors. In Proceedings of the 2000 Congress on Evolutionary Computation, volume 1, pages 384–391, La Jolla, CA, USA, 16.-19.July 2000. IEEE, Piscataway, NJ. * www/IEEE ga00aPRHarvey. [542] Peter Stagge and Christian Igel. Evolution strategies: An alternative to gradient based learning. In X. Yao and D. B. Fogel, editors, 2000 IEEE Symposium on Combinations of Evolutionary Computation and Neural Networks (ECNN), volume ?, pages 82–90, Piscataway, NJ, ? 2000. IEEE Press. †Wiegand ga00aPStagge. [543] Rameri Salama. On Evolving Modular Neural Networks. PhD thesis, University of West Australia, Department of Computer Science, 2000. (http://www.cs.uwa.edu.au/pub/robvis/theses/RameriSalama. ps.gz) * GAdigest v 15 n 7 ga00aRameriSalama. [544] Robert H. Kewley, Mark J. Embrecths, and Curt Breneman. Data strip mining for the virtual design of pharmaceuticals with neural networks. IEEE Transactions on Neural Networks, 11(3):668–679, May 2000. ga00aRHKewley. [545] R. Neruda. Genetic algorithms and neural networks - making use of parameter space symmetries. In S. Amari, C. L. Giles, M. Gori, and V. Piuri, editors, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, volume 1, pages 293–298, Como, Italy, 24.-27.July 2000. IEEE Computer Soc., Los Alamitos. †P90178 ga00aRNeruda. [546] Randall S. Sexton and Jatinder N. D. Gupta. Comparative evaluation of genetic algorithm and backpropagation for training neural networks. Information Sciences, 129(1-4):45–59, November 2000. ga00aRSSexton. [547] S. Bell, E. Nazarov, Y. F. Wang, J. E. Rodriguez, and G. A. Eiceman. Neural network recognition of chemical class information in mobility spectra obtained at high temperatures. Anal. Chem., 72(6):1192– 1198, 15. March 2000. * PubMed10740859 ga00aSBell. [548] Sara Pozzi and Javier Segovia. Evaluation of genetic programming and neural networks techniques for nuclear material identification. pages 590–596, 2000. ga00aSPozzi. [549] Sushmita Mitra and Yoichi Hayashi. Neuro-fuzzy rule generation: survey in soft computing framework. IEEE Transactions on Neural Networks, 11(3):748–768, May 2000. ga00aSushmitaMitra. [550] Tony Abou-Assaleh and Jianna Zhang. Autonomous life agent using recurrent neural networks and genetic algorithms. pages 1–5, 2000. ga00aTAbou-Assaleh. [551] T. Aikawa. Nonlinear time-series analysis of pulsation of post-AGB stars by genetic algorithm/neural network hybrid systems. In L. Szabados and D. Kurtz, editors, The Impact of Large-Scale Surveys on Pulsating Star Research, ASP Conference Series, volume 203, pages 135–136, ?, ? 2000. ? †NASA ADS ga00aTAikawa. [552] Thomas Ragg. Problemlösung durch Komitees neuronaler Netze. PhD thesis, University of Karlsruhe, Department of Computer Science, 2000. * www ga00aThomasRagg. [553] Ting-Yu Chen and Chia-Yang Lin. Determination of optimum design spaces for topology optimization. Finite Elements in Analysis and Design, 36(1):1–16, 1. August 2000. * A01-10295/01 ga00aTing-YuChen. [554] T. S. Bi, Y. X. Ni, C. M. Chen, and F. F. Fu. A novel ANN fault diagnosis system for power system using dual GA loops in ANN training. In IEEE Power Engineering Society Summer Meeting, volume 1, pages 425–430, Seattle, WA, USA, 16.-20.July 2000. IEEE, Piscataway, NJ. * www/IEEE ga00aTSBi. [555] T. Senjyu, Y. Tamaki, and K. Uezato. Next day load curve forecasting using self organizing map. In Kit Po Wong, Su Q, B. Stewart, and X. Zhou, editors, Proceedings. International Conference on Power System Technology. PowerCon 2000, volume 2, pages 1113–1118, Perth, WA, Australia, 4.-7.December 2000. IEEE, Piscataway, NJ. * www/IEEE ga00aTSenjyu. [556] T. Smith and A. Philippides. Mitric oxide signalling in real and artificial neural networks. BT Technology Journal, 18(4):1400–149, October 2000. * ga00aTSmith. 90 Genetic algorithms and neural networks [557] T. Villmann, R. Haupt, and E. Hering. Parallel evolutionary algorithms with SOM-like migration and its application to VLSI design. In S. Amari, C. L. Giles, M. Gori, and V. Piuri, editors, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks, volume 5, pages 167–172, Como, Italy, 24.-27.July 2000. IEEE Computer Soc., Los Alamitos. †P90182 ga00aTVillmann. [558] V. M. Preciado, D. Guinea, J. Vicente, M. C. Garcia-Alegre, and A. Ribeiro. Automatic CNN multitemplate tree generation. In Proceedings of the 2000 6th IEEE International Workshop on Cellular Neural Networks and Their Applications (CNNA 2000), pages 327–332, Catania (Italy), 23.-25. May 2000. IEEE, Piscataway, NJ. * www /IEEE ga00aVMPreciado. [559] X. G. Ming and K. L. Mak. A hybrid Hopfield network-genetic algorithm approach to optimal process plan selection. International Journal of Production Research, 38(8):1823–1839, May 2000. ga00aXGMing. [560] Xiao-Zhi Gao, Seppo J. Ovaska, and Y. Dote. Motor fault detection using Elman neural network with genetic algorithm-aided training. In Proceedings of the 2000 IEEE International Conference on Systems, Man, and Cybernetics, volume 4, pages 2386–2392, ?, ? 2000. IEEE, Piscataway, NJ. ga00aXiao-ZhiGao. [561] Xiaoqin Yang and Ming Li. Using Hopfield neural network and 2D evolutionary operators to detect image edge. In Feijun Song, Frank Chen, Michael Y. Hung, and H. M. Shang, editors, Optical Measurement and Nondestructive Testing: Techniques and Applications, volume SPIE-4221, pages 292–295, ?, October 2000. The International Society for Optical Engineering. * www/SPIE Web ga00aXYang. [562] X. Z. Gao, S. J. Ovaska, and Y. Dote. Motor fault detection using Elman neural network with genetic algorithm-aided training. In IEEE International Conference on Systems, Man, and Cybernetics, volume 4, pages 2386–2392, Nashville, TN, USA, 8.-11.October 2000. IEEE, Piscataway, NJ. * www/IEEE ga00aXZGao. [563] Yen-Wei Chen, Xiang-Yan Zeng, Zensho Nakao, and Katsumi Yamashita. Independent component analysis by evolutionary neural networks. In Nasser M. Nasrabadi and Aggelos K. Katsaggelos, editors, Applications of Artificial Neural Networks in Image Processing V, volume SPIE-3962, pages 83–90, ?, April 2000. The International Society for Optical Engineering. * www/SPIE Web ga00aY-WChen. [564] Y. Mitsukura, M. Fukumi, and N. Akamatsu. Design and evaluation of neural networks for coin recognition by using GA and SA. In S. Amari, C. L. Giles, M. Gori, and V. Piuri, editors, Proceedings of the IEEEINNS-ENNS International Joint Conference on Neural Networks, volume 5, pages 178–186, Como, Italy, 24.-27.July 2000. IEEE Computer Soc., Los Alamitos. †P90182 ga00aYMitsukura. [565] Fabrizio Russo. Noise removal from image data using recursive neurofuzzy filters. IEEE Transactions on Instrumentation and Measurement, 49(2):307–314, April 2000. ga00bFRusso. [566] M.-W. Suh and M.-B. Shim. Crack identification using hybrid neuro-genetic technique. Journal of Sound and Vibration, 238(4):617–635, 7. December 2000. * A01-34664 ga00bM-WSuh. [567] Michael Hüsken and Christian Goerick. Fast learning for problem classes using knowledge based network initialization. In Sun-Ichi Amari, C. Lee Giles, Marco Gori, and Vincenzo Piuri, editors, Proceedings of the International Joint Conference on Neural Networks (IJNN 2000), volume VI, pages 619–624, Como (Italy), ? 2000. IEEE Computer Society Press, Los Alamitos, CA. ga00bMichaelHusken. [568] Martin Kreutz. Modellierung von unvollständig beschriebenen Systemen. Ibidem-Verlag, ?, 2000. †Wiegand ga00bMKreutz. [569] Jordan B. Pollack and Hod Lipson. The GOLEM project: Evolving hardware bodies and brains. In Jason Lohn, Adrian Stoica, Didier Keymeulen, and Silvano Colombano, editors, Proceedings of the Second NASA/DoD Workshop on Evolvanle Hardware, pages 37–42, Palo Alto, CA, 13.-15. July 2000. IEEE Computer Society. ga00bPollack. [570] Tomonobu Senjyu, Shotaro Tamane, and Katsumi Uezato. Adaptive control for multi-machine power systems using genetic algorithm and neural network. In IEEE Power Engineering Society Winter Meeting, volume 2, pages 1342–1347, Singapore, 23.-27. January 2000. IEEE, Piscataway, NJ. ga00bTSenjyu. [571] Vesselin K. Vassilev, Dominic Job, and Julian F. Miller. Towards the automatic design of more efficient digital circuits. In Jason Lohn, Adrian Stoica, Didier Keymeulen, and Silvano Colombano, editors, Proceedings of the Second NASA/DoD Workshop on Evolvanle Hardware, pages 151–160, Palo Alto, CA, 13.-15. July 2000. IEEE Computer Society. ga00bVKVassilev. [572] Ron Wehrens and Lutgarde M. C. Buydens. Chapter 6. chemometrics. pages 99–114. 2000. ga00bWehrens. [573] Y.-W. Chen, X.-Y. Zeng, and Z. Nagao. Blind separation based on an evolutionary neural network. In A. Sanfeliu, J. J. Villanueva, M. Vanrell, R. Alquezar, J.-O. Eklundh, and Y. Aloimonos, editors, 15th International Conference on Pattern Recognition , 2000, volume 2, pages 973–976, Barcelona, Spain, 3.7.September 2000. IEEE, Piscataway, NJ. * www/IEEE ga00bY-WChen. Bibliography 91 [574] Michael Hüsken and Bernhard Sendhoff. Evolutionary optimization for problem classes with Lamarckian inheritance. In Soo-Young Lee, editor, Seventh International Conference on Neural Information processing (ICONIP 2000) - Proceedings, pages 897–902, Taejon (South Korea), ? 2000. ? ga00cMichaelHusken. [575] A. Blanco, M. Delgado, and M. C. Pegalajar. A real-coded genetic algorithm for training recurrent neural networks. Neural Networks, 14(1):93–105, January 2001. ga01aABlanco. [576] Alaa F. Sheta and Kenneth A. De Jong. Time-series forecasting using GA-tuned radial basis functions. Information Sciences, 133(?):221–228, ? 2001. * TKKpaa ga01aAFSheta. [577] Alioune Ngom, Ivan Stojmenović, and Veljko Milutinoviv́. STRIP - a strip-based neural-network growth algorithm for learning multiple-valued functions. IEEE Transactions on Neural Networks, 12(2):212–227, March 2001. ga01aANgom. [578] A. Sierra, J. A. Macias, and F. Corbacho. Evolution of functional link networks. IEEE Transactions on Evolutionary Computation, 5(1):54–65, February 2001. * www /IEEE ga01aASierra. [579] C. A. Perez, C. Salinas, and P. Estevez. Designing biologically inspired receptive fields for neural pattern recognition technology. In Proceedings of the 2001 IEEE International Conference on System, Man, and Cybernetics, volume 1, pages 58–63, Tuczon, AZ, 7.-10 October 2001. IEEE, Piscataway, NJ. * www /IEEE ga01aCAPerez. [580] Candida Ferreira. Gene expression programming: A new adaptive algorithm for solving problems. Complex Systems, 13(2):87–129, 2001. †Ferreira ga01aCFerreira. [581] Christian Igel, Wolfram Erlhagen, and Dirk Jancke. Optimization of neural field models. Neurocomputing, 36(1-4):225–233, ? 2001. ga01aChristianIgel. [582] Christopher MacLeod and Grant M. Maxwell. Incremental evolution in ANNs: Neural nets which grow. Artificial Intelligence Review, 16(3):201–224, November 2001. ga01aCMacLeod. [583] E. A. Saci and Y. Cherruault. The genicAgent: a hybrid approach for multi-agent problem solving. Kybernetes, 30(1-2):26–34, 2001. * ISI ga01aEASaci. [584] Fengzhan Tian, Yuchang Lu, and Chunyi Shi. Learning Bayesian networks with hidden variables using the combination of EM and evolutionary algorithms. In David Cheung, Graham J. Williams, and Qing Li, editors, Advances in Knowledge Discovery and Data Mining, Proceedings of the 5th Pacific-Asia Conference, PAKDD 2001, volume 2035 of Lecture Notes in Artificial Intelligence, pages 568–574, Hong Kong (China), 16.-18. April 2001. Springer-Verlag, Berlin. ga01aFengzhanTian. [585] Gary G. Yen and Phayung Meesad. Development of a neuro-fuzzy expert system for predictive maintenance. In Peter K. Willett and Thiagalingam Kirubarajan, editors, Component and Systems Diagnostics, Prognosis, and Health Management, volume SPIE-4389, pages 138–149, ?, July 2001. The International Society for Optical Engineering. * www/SPIE Web ga01aGGYen. [586] Hugo de Garis, Andrzej Buller, Leo de Penning, Tomasz Chodakowski, and Derek Decesare. Initial evolution results on CAM-brain machines (CBMs). In G. Dorffner, H. Bischof, and K. Hornik, editors, Artificial Neural Networks - ICANN 2001, International Conference, volume LNCS of 2130, pages 814–819, Vienna (Austria), 21.-25. August 2001. Springer-Verlag Berlin Heidelberg. * www /Springer ga01aHdeGaris. [587] H. Edelbrunner, U. Handmann, I. Igel, I. Leefken, and W. von Seelen. Application and optimization of neural field dynamics for driver assistance. In Proceedings of the IEEE 4th International Conference on Intelligent Transportation Systems (ITSC’01), pages 309–314, Oakland, CA, ? 2001. IEEE Press, Piscataway, NJ. ga01aHEdelbrunner. [588] Hisao Ishibuchi, Tomoharu Nakashima, and M. Nii. Learning of neural networks with GA-based instance seletion. In M. H. Smith, W. A. Gruver, and L. O. Hall, editors, Joint 9th IFSA World Cingress and 20th NAFIPS International Conference, volume 4, pages 2102–2107, Vancouver, BC, Canada, 25.-28.July 2001. IEEE, Piscataway, NJ. * www/IEEE ga01aHIshibuchi. [589] I. Aizenberg, N. Aizenberg, J. Hiltner, C. Moraga, and E. Meyer zu Bexten. Cellular neural networks and computational intelligence in medical image processing. Image and Vision Computing, 19(4):177–183, March 2001. ga01aIAizenberg. [590] Auke Jan Ijspeert. A connectionist central pattern generator for the aquatic and terrestrial gaits of a simulated salamander. Biological Cybernetics, 84(5):331–348, 12. April 2001. * EBSCO ga01aIjspeert. [591] Ingrid M. Schleiter, M. Obach, D. Borchardt, and H. Werner. Bioindication of chemical and hydromorphological habitat characteristics with benthic macro-invertebrates based on artificial neura networks. Aquatic Ecology, 35(2):147–158, June 2001. ga01aIMSchleiter. 92 Genetic algorithms and neural networks [592] I. Sekaj. Genetic algorithm based design of a neural controller. In Matoušek Radek and Ošmera Pavel, editors, 7th International Conference on Soft Computing, Mendel 2001, pages 341–344, Brno, Czech Republic, 6.- 8.June 2001. Brno University of Technology. ga01aISekaj. [593] Ji-Cheng Duan and Fu-Lai Chung. Cascaded fuzzy neural network model based on syllogistic fuzzy reasoning. IEEE Transactions on Fuzzy Systems, 9(2):293–306, April 2001. ga01aJ-CDuan. [594] J. Arifovic and R. Gencay. Using genetic algorithms to select architecture of a feedforward artificial neural network. Physica A, 289(3-4):574–594, January 2001. †NASA ADS ga01aJArifovic. [595] Joshua A. Singer. Co-evolving a neural-net evaluation function for Othello by combining genetic algorithms and reinforcement learning. In V. N. Alexandrov, J. J. Dongarra, B. A. Juliano, R. S. Renner, and C. J.Kenneth Tan, editors, Computational Science - ICCS 2001, International Conference, volume LNCS of 2074, pages 377–389, San Francisco, CA, 28.-30. May 2001. Springer-Verlag Berlin Heidelberg. * www /Springer ga01aJASinger. [596] Junhua Liu, Yong Zhang, and Ming Chen. Cross sensitivity reduction of gas sensors using genetic algorithm neural network. In Stuart Farquharson, editor, Optical Methods for Industrial Processes, volume SPIE4201, pages 24–32, ?, February 2001. The International Society for Optical Engineering. * www/SPIE Web ga01aJLiu. [597] José L. Sanz-González and Diego Andina. Importance sampling techniques in neural detector training. In L. De Raedt and P. Flach, editors, Machine Learning: EMCL 2001, 12th European Conference on Machine Learning, volume LNAI of 2167, pages 431–441, Freiburg (Germany), 5.-7. September 2001. Springer-Verlag Berlin Heidelberg. * www /Springer ga01aJLSanz-Gonzalez. [598] Jorge Muruzábal. Evolving high-posterior self-organizing maps. In J. Mira and A. Prieto, editors, Connectionist Models of Neurons, Learning Processes and Artificial Intelligence, 6th International WorkConference on Artificial and Natural Neural Networks, IWANN 2001, volume LNCS of 2084, pages 701–709, Granada (Spain), 13.-15. June 2001. Springer-Verlag Berlin Heidelberg. * www /Springer ga01aJMuruzabal. [599] Jongsoo Lee and Prabhat Hajela. Application of classifier system in improving response surface based approximations for design optimization. Computers & Structures, 79(?):333–344, ? 2001. ga01aJongsooLee. [600] J. Santos, R. J. Duro, J. A. Becerra, J. L. Crespo, and F. Bellas. Considerations in the application of evolution to the generation of robot controllers. Information Sciences, 133(?):127–148, ? 2001. * TKKpaa ga01aJSantos. [601] J. S. Kirk and J. M. Zurada. An evolutionary method of training topography-preserving maps. In International Joint Conference on Neural Networks, 2001. IJCNN ’01, volume 3, pages 2230–2234, Washington, DC, USA, 15.-19.July 2001. IEEE, Piscataway, NJ. * www/IEEE ga01aJSKirk. [602] K. KrishnaKumar, Y. Yachisako, and Y. Huang. Jet engine performance estimation using intelligent system technologies. In AIAA Aerospace Sciences Meeting and Exhibit, Reno, NV, 8.-11. January 2001. AIAA. AIAA Paper 2001-1122 * A01-16903 ga01aKKrishnaKumar. [603] Marc Thuillard. Wavelets in Soft Computing, volume 25 of Robotics and Intelligent Systems. World Scientific, Singapore, 2001. ga01aMarcThuillard. [604] Markus Brameier and Wolfgang Banzhaf. A comparison of linear genetic programming and neural networks in medical data mining. IEEE Transactions on Evolutionary Computation, 5(1):17–26, February 2001. ga01aMBrameier. [605] M. F. Jefferson, S. Burlinson, A. Burns, D. Mann, S. Pickering-Brown, F. Owen, C. Sriwardhana, N. Pendleton, and M. A. Horan. Clinical features of dementia associated with apolipoprotein epsilon4: Discrimination with a neural network genetic algorithm. International Journal of Geriatric Psychiatry, 16(1):77–81, January 2001. * ISI PsycINFO 2001-14382-009 ga01aMFJefferson. [606] Michael Hüsken, Christian Igel, and Marc Toussaint. Task-dependent evolution of modularity in neural networks – a quantitative case study. In Erik D. Goodman, editor, 2001 Genetic and Evolutionary Computation Conference (GECCO 2001) – Late-Breaking Papers, pages 187–193, San Francisco, CA, ? 2001. ? ga01aMichaelHusken. [607] Matthew J. Steeter, Matthew O. Ward, and Sergio A. Alvarez. NVIS: an interactive visualization tool for neural networks. In Robert F. Erbacher, Philip C. Chen, Jonathan C. Roberts, Craig M. Wittenbrink, and Matti Groehn, editors, Visual Data Exploration and Analysis III, volume SPIE-4302, pages 234–241, ?, May 2001. The International Society for Optical Engineering. * www/SPIE Web ga01aMJStreeter. Bibliography 93 [608] Mark Lilichenko and Anne Myers Kelley. Application of artificial neural networks and genetic algorithms to modeling molecular electronic spectra in solution. The Journal of Chemical Physics, 114(16):7094–7102, April 2001. †NASA ADS ga01aMLilichenko. [609] M. S. A. Oliveira and A. C. M. Sousa. Neural network analysis of experimental data for air/water spray cooling. Journal of Materials Processing Technology, 113(1-3):439–445, 15. June 2001. ga01aMSAOliveira. [610] Md Sah Hj Salam, Dzulkifli Mohamad, and Sheikh Hussain Sheikh Salleh. Neural network speaker dependent isolated Malay speech recognition system: handcrafted vs genetic algorithm. In ?, editor, International Symposium on Signal Processing and its Applications (ISSPA), volume ?, pages 731–734, Kuala Lumpur, Malaysia, 13.-16. August 2001. ? ga01aMSHSalam. [611] M. Sugawara. Numerical solution of the Schrödinger equation by neural network and genetic algorithm. Computer Physics Communications, 140(3):366–380, November 2001. ga01aMSugawara. [612] N. Butuk and J.-P. Pemba. Computing low dimensional invariant manifolds of reaction mechanism using genetic algorithms. In AIAA Aerospace Sciences Meeting and Exhibit, Reno, NV, 8.-11. January 2001. AIAA. AIAA Paper 2001-1076 * A01-16861 ga01aNButuk. [613] N. Chaiyaratana and K. Boonlong. Further investigations on friction compensation using a neuro-genetic based hybrid framework. In Joint 9th IFSA World Congress and 20th NAFIPS International Conference, volume 5, pages 2772–2777, Vancouver, BC, Canada, 25.-28. July 2001. IEEE, Piscataway, NJ. ga01aNChaiyaratana. [614] O. M. Lewis, J. A. Ware, and D. H. Jenkins. Identification of residential property sub-markets using evolutionary and neural computing techniques. Neural Computing & Applications, 10(2):108–119, ? 2001. * www /Springer ga01aOMLewis. [615] Oliver Nelles. Nonlinear System Identification: from Classical Approaches to Neural Networks and Fuzzy Models. Springer-Verlag, Berlin, 2 edition, 2001. †www /Springer ga01aONelles ⇒ http://worldcat. org/wcpa/oclc/44883772. [616] P. Meesad and G. G. Yen. A hybrid intelligent system for medical diagnosis. In Proceedings of the International Joint Conference on Neural Networks (IJCNN’01), volume 4, pages 2558–2563, Washington, DC, 15.-19. July 2001. IEEE, Piscataway, NJ. * www /IEEE ga01aPMeesad. [617] Patricia Melin and Oscar Castillo. Intelligent control of complex electrochemical systems with a neurofuzzy-genetic approach. IEEE Transactions on Industrial Electronics, 48(5):951–955, October 2001. ga01aPMelin. [618] Pavlov S. Georgilakis, Nikilaos D. Doulamis, Anastasios D. Doulamis, Nikos D. Hatziargyriou, and Stefanos D. Kollias. A novel iron loss reduction technique for distribution transformer based on a combined genetic algorithm - neural network approach. IEEE Transactions on Systems, Man, and Cybernetics Part C: Applications and Reviews, 31(1):16–34, February 2001. ga01aPSGeorgilakis. [619] Peter Stagge and Christian Igel. Structure optimisation and isomorphisms. In Leila Kallel, B. Naudts, and A. Rogers, editors, Theoretical Aspects of Evolutionary Computing, pages 409–422. Springer-Verlag, ?, 2001. ? †Wiegand ga01aPStagge. [620] Richard F. Stoisits, Kelly D. Crawford, Donald J. MacAllister, and Michael D. McCormack. Petroleum production optimization utilizing adaptive network and genetic algorithm techniques, 2001. (U. S. patent no. 6,236,894. Issued May 22 2001; http://appft1.uspto.gov/netahtml/PTO/search-adv.html) ga01aRFStoisits. [621] R. J. Kuo. A sales forecasting system based on fuzzy neural network with initial weights generated by genetic algorithm. European Journal of Operational Research, 129(3):496–517, 16. March 2001. ga01aRJKuo. [622] R. S. Sexton, M. A. Hignite, T. Margavio, and J. Satzinger. Neural networks refined: using a genetic algorithm to identify predictors of IS student success. Journal of Computer Information Systems, 41(3):42– 47, Spring 2001. * ISI ga01aRSSexton. [623] Sang-Woo Moon and Seong-Gon Kong. Block-based neural networks. IEEE Transactions on Neural Networks, 12(2):307–317, March 2001. ga01aS-WMoon. [624] S. L. Mok, C. K. Kwong, and W. S. Lau. A hybrid neural network and genetic algorithm approach to the determination of initial process parameters for injection moulding. The International Journal of Advanced Manufacturing Technology, 18(6):404–409, 2001. ga01aSLMok. [625] Spyros Raptis, Spyros Tzafestas, and Hermione Karagianni. Optimal genetic representation of complete strictly-layered feedforward neural networks. In J. Mira and A. Prieto, editors, Bio-Inspired Applications 94 Genetic algorithms and neural networks of Connectionism, 6th International Work-Conference on Artificial and Natural Neural Networks, IWANN 2001, volume LNCS of 2085, pages 127–135, Granada (Spain), 13.-15. June 2001. Springer-Verlag Berlin Heidelberg. * www /Springer ga01aSRaptis. [626] Stephen Soliday, Melissa T. Perona, and Daniel G. McCauley. Hybrid fuzzy-neural classifier for feature level data fusion in ladar autonomous target recognition. In Firooz A. Sadjadi, editor, Automatic Target Recognition XI, volume SPIE-4379, pages 66–77, ?, October 2001. The International Society for Optical Engineering. * www/SPIE Web ga01aSSoliday. [627] S. Sural and P. K. Das. A genetic algorithm for feature selection in a neuro-fuzzy OCR system. In Sixth International Conference on Document Analysis and Recognition, 2001, volume ?, pages 987–991, Seattle, WA, USA, 10.-13.September 2001. IEEE, Piscataway, NJ. * www/IEEE ga01aSSural. [628] Takahisa Kobatashi and Donald L. Simon. A hybrid neural network-genetic algorithm technique for aircraft engine performance diagnostics. In 37th AIAA/ASME/SAE/ASEE Joint Propulsion Conference and Exhibit, Salt Lake City, UT, 8.-11. July 2001. AIAA. AIAA Paper 2001-3757 * A01-34418 ga01aTakahisaKobatashi. [629] Thomas Ragg. Bayesian learning and evolutionary parameter optimization. In F. Baader, G. Brewka, and T. Eiter, editors, KI 2001, volume 2174 of Lecture Notes in Artificial Intelligence, pages 48–62, Berlin, ? 2001. Springer-Verlag. ga01aThomasRagg. [630] T. Ichimura, S. Oeda, and K. Yoshida. An adaptive evolutional neuro learning method using genetic search and extraction of rules from trained networks. In Proceedings of the 2001 Congress on Evolutionary Computation, volume 2, pages 1343–1350, Seoul, South Korea, 27.-30.May 2001. IEEE, Piscataway, NJ. * www/IEEE ga01aTIchimura. [631] Trandarif Moisa, Dan Ontanu, and Adrian Horia Dediu. Speech synthesis using neural networks trained by an evolutionary algorithm. In V. N. Alexandrov, J. J. Dongarra, B. A. Juliano, R. S. Renner, and C. J.Kenneth Tan, editors, Computational Science - ICCS 2001, International Conference, volume LNCS of 2074, pages 419–428, San Francisco, CA, 28.-30. May 2001. Springer-Verlag Berlin Heidelberg. * www /Springer ga01aTMoisa. [632] Thomas R. Cundari and Marco Russo. Database mining using soft computing techniques. an integrated neural network-fuzzy logic-genetic algorithm approach. Journal of Chemical Information and Computer Sciences, 41(2):281–287, March/April 2001. ga01aTRCundari. [633] Tom Smith, Phil Husbands, and Michael O’Shea. Neutral networks and evolvability with complex genotypephenotype mapping. In J. Kelemen and P. Sosı́k, editors, Advances in Artificial Life, 6th European Conference, ECAL 2001, volume LNAI of 2159, pages 272–281, Prague (Czech Republic), 10.-14. September 2001. Springer-Verlag Berlin Heidelberg. * www /Springer ga01aTSmith. [634] U. Markowska. On application of genetic algorithm to rule extraction from trained neural networks. In Matoušek Radek and Ošmera Pavel, editors, 7th International Conference on Soft Computing, Mendel 2001, pages 70–74, Brno, Czech Republic, 6.- 8.June 2001. Brno University of Technology. ga01aUMarkowska. [635] Victor M. Preciado, Domingo Guinea, and Rodrigo Montufar-Chaveznava. Automatic generation of multipath algorithms in the cellular nonlinear network. In Nasser M. Nasrabadi and Aggelos K. Katsaggelos, editors, Applications of Artificial Neural Networks in Image Processing VI, volume SPIE-4305, pages 149–159, ?, April 2001. The International Society for Optical Engineering. * www/SPIE Web ga01aVMPreciado. [636] Wen-Lan Wu, Fong-Chin Su, Yuh-Min Cheng, and You-Li Chou. Potential of the genetic algorithm neural network in the assessment of gait patterns in ankle artrodesis. Annals of Biomedical Engineering, 29(1):83–91, 2001. ga01aWen-LanWu. [637] Walker H. Land, Timothy D. Masters, Joseph Y. Lo, and Dan McKee. Application of adaptive boosting to EP-derived multilayer feed-forward neural networks MLFN to improve benign/malignant breast cancer classification. In Milan Sonka and Kenneth M. Hanson, editors, Medical Imaging 2001: Image Processing, volume SPIE-4322, pages 1717–1724, ?, July 2001. The International Society for Optical Engineering. * www/SPIE Web ga01aWHLand. [638] W. Martins and J. Carlos Meira e Silva. Multidimensional data ranking using self-organising maps and genetic algorithms. In International Joint Conference on Neural Networks. IJCNN ’01, volume 4, pages 2382–2387, Washington, DC, USA, 15.-19.July 2001. IEEE, Piscataway, NJ. * www/IEEE ga01aWMartins. [639] Xiaodan Mei and Sheng-He Sun. Comparison of neuron selection algorithms of wavelet-based neural network. In Xubang Shen and Jianguo Liu, editors, Neural Network and Distributed Processing, volume SPIE-4555, pages 121–126, ?, September 2001. The International Society for Optical Engineering. * www/SPIE Web ga01aXMei. Bibliography 95 [640] Ying Tan and Jun Wang. Nonlinear blind source separation using higher order statistics and a genetic algorithm. IEEE Transactions on Evolutionary Computation, 5(6):600–612, December 2001. ga01aYTan. [641] Zümray Dokur and Tamer Ölmez. ECG beat classification by a novel hybrid neural network. Computer Methods and Programs in Biomedicine, 66(?):167–181, ? 2001. ga01aZDokur. [642] Zhou Hao, Cen Kefa, and Mao Jianbo. Combining neural network and genetic algorithms to optimize low NOx pulverized coal combustion. Fuel, 80(?):2163–2169, ? 2001. ga01aZhouHao. [643] A. A. Attia and P. Horáček. An optimal design of fuzzy logic neural network using linear adapted genetic algorithm. In Matoušek Radek and Ošmera Pavel, editors, 7th International Conference on Soft Computing, Mendel 2001, pages 32–49, Brno, Czech Republic, 6.- 8.June 2001. Brno University of Technology. ga01bAAAttia. [644] C. A. Perez, G. D. Gonzalez, and C. Salinas. Genetic selection of non-linear product terms in the input to a linear classifier for handwritten digit recognition. In Proceedings of the 2001 IEEE International Conference on System, Man, and Cybernetics, volume 4, pages 2337–2342, Tuczon, AZ, 7.-10 October 2001. IEEE, Piscataway, NJ. * www /IEEE ga01bCAPerez. [645] Christian Igel and Werner von Seelen. Design of a field model for early vision: A case study of evolutionary algorithms in neuroscience. In 28th Göttingen Neurobiology Conference, page 1034, Göttingen (Germany), ? 2001. George Thieme Verlag. ga01bChristianIgel. [646] Julian Dorado, Antonio Santos, and Juan R. Rabuñal. Multilevel genetic algorithm for the complete development of ANN. In J. Mira and A. Prieto, editors, Connectionist Models of Neurons, Learning Processes and Artificial Intelligence, 6th International Work-Conference on Artificial and Natural Neural Networks, IWANN 2001, volume LNCS of 2084, pages 717–724, Granada (Spain), 13.-15. June 2001. Springer-Verlag Berlin Heidelberg. * www /Springer ga01bJDorado. [647] Jimin Liang, Heng Zhao, and Wanhai Yang. Designing neuroclassifier fusion systems by immune genetic algorithm. In Jun Shen, Sharatchandra Pankanti, and Runsheng Wang, editors, Object Detection, Classification, Tracking Technologies, volume SPIE-4554, pages 124–129, ?, September 2001. The International Society for Optical Engineering. * www/SPIE Web ga01bJiminLiang. [648] Man Gyun Na, Won Sik Yang, and Hangbok Choi. Pin power reconstruction for CANDU reactors using a neuro-fuzzy inference system. IEEE Transactions on Nuclear Science, 48(2):194–201, April 2001. ga01bMGNa. [649] Chi-Hsu Wang, Han-Leih Liu, and Chin-Teng Lin. Dynamic optimal learning rates of a certain class of fuzzy neural networks and its applications with genetic algorithm. IEEE Transactions on Systems, Man and Cybernetics - Part B: Cybernetics, 31(3):467–475, June 2001. ga01C-HWang. [650] Christian Igel and Martin Kreutz. Operator adaptation in structure optimization of neural networks. In Lee Spector, Erik D. Goodman, A. Wu, William B. Langdon, Hans-Michael Voig, M. Gen, Marco Dorigo, S. Pezeshk, M. Garzon, and E. Burke, editors, Genetic and Evolutionary Computation Conference (GECCO 2001), page 1094, San Francisco, CA, ? 2001. Morgan Kaufmann, SanFrancisco, CA. ga01cChristianIgel. [651] Christian Igel and Martin Kreutz. Operator adaptation in evolutionary computation and its application to structure optimization of neural networks. Internal Report IRINI 01-03, Institut für Neuroinformatik, 2001. ? †Wiegand ga01dChristianIgel. [652] Andrew Skabar and Ian Coete. Neural networks, financial trading and the efficient markets hypothesis. In ?, editor, Proceedings of the 25th Australasian Conference on Computer Science, volume 4, pages 241– 249, Melbourna, Victoria, Australia, ? 2002. Australian Computer Society, Inc., Darlinghurst, Australia. ga02aAndrewSkabar. [653] Alessandro Salvini and Francesco Riganti Fulginei. Genetic algorithms and neural networks generalizing the Jiles-Atherton model of static hysteresis for dynamic loops. IEEE Transactions on Magnetics, 38(2):873– 876, March 2002. ga02aASalvini. [654] Barry K. Lavine, C. E. Davidson, and Anthony J. Moores. Innovative genetic algorithms for chemoinformatics. Chemometrics and Intelligent Laboratory Systems, 60(1-2):161–171, 28. January 2002. ga02aBarryKLavine. [655] Bernd Dachwald. Optimization of interplanetary rendezvous trajectories for solar sailcraft using a neurocomputer. In AIAA/AAS Astrodynamics Specialist Conference and Exhibit, Monterey, CA, 5.-8. August 2002. AIAA. AIAA Paper 2002-4989 * A02-38308 ga02aBDachwald. [656] B. J. Sung, J. W. Park, and Y. H. Kim. Material property identification of composite plates using neural network and evolution algorithm. AIAA Journal, 40(9):1914–1916, September 2002. * A02-38717 ga02aBJSung. 96 Genetic algorithms and neural networks [657] Benyamin Kusumoputro, Martha Y. Pangabean, and Leila F. Rachman. Genetic algorithms in optimization of 3D face recognition system using cylindrical-hidden layer neural network in its eigenspace domain. In Kevin G. Harding and John W. Miller, editors, Machine Vision and Three-Dimensional Imaging Systems for Inspection and Methodology II, volume SPIE-4567, pages 84–93, ?, February 2002. The International Society for Optical Engineering. * www/SPIE Web ga02aBKusumoputro. [658] Chia-Feng Juang. A TSK-type recurrent fuzzy network for dynamic systems processing by neural network and genetic algorithms. IEEE Transactions on Fuzzy Systems, 10(2):155–170, April 2002. ga02aC-FJuang. [659] Chao-Ton Su and Tai-Lin Chiang. Optimal design for a ball grid array wire bonding process a neuralgenetic approach. IEEE Transactions of Electronics Packaging Manufacturing, 25(1):13–18, January 2002. ga02aC-TSu. [660] C. Shunmuga Velayutham, Sandeep Paul, and Satish Kumar. Evolutionary subsethood product fuzzy neural network. In N. R. Pal and M. Sugeno, editors, Advances in Soft Computing - AFSS 2002, 2002 AFSS International Conference on Fuzzy Systems, volume LNAI of 2275, pages 274–280, Calcutta (India), 3.-6. February 2002. Springer-Verlag Berlin Heidelberg. * www /Springer ga02aCSVelayutham. [661] Daryl Essam. Book review: Blondie24: Playing at the Edge of AI. Genetic Programming and evolvable Machines, 3(4):389–390, December 2002. ga02aDarylEssam. [662] B. D. Hutt. Innate Intelligence for Artificial Organisms: via Species Evolution of Neural Networks. PhD thesis, University of Reading, 2002. †refereed paper ga02aDBHutt. [663] David M. Rodvold. Method for simultaneously optimizing artificial neural network inputs and architectures using genetic algorithms, 2002. (U.S. patent no. 2002/0059154. Issued May 16 2002) ga02aDMRodvold. [664] Donald A. Sofge. Using genetic algorithm based variable selection to improve neural network models for real-world systems. In ?, editor, Proceedings of the 2002 International Conference on Machine Learning and Applications, pages –, ?, ? 2002. ? ga02aDonaldASofge. [665] D. Vergados, C. Anagnostopoulos, I. Anagnostopoulos, J. Soldatos, E. Kayafas, V. Loumos, and G. Stassinopoulos. Neural networks for routing optimization in wideband networks. pages 173–178, 2002. ga02aDVergados. [666] V. David Sànchez. Searching for a solution to the automatic RBF network design problem. Neurocomputing, 42(1-4):147–170, January 2002. †www /Elsevier ga02aDVSanchez. [667] Devert Wicker, Mateen M. Rizki, and Louis A. Tamburino. E-Net: Evolutionary neural network synthesis. Neurocomputing, 42(1-4):171–196, January 2002. †www /Elsevier ga02aDWicker. [668] E. Gómez-Ramı́rez and X. Vilasis-Cardona. Adaptive multiresolution filtering to forecast nonlinear time series. In Neural Networks, 2002. IJCNN ’02. Proceedings of the 2002 International Joint Conference on, volume 1, pages 400–405. IEEE, Piscataway, NJ, 12.-17. May 2000. ga02aEGomez-Ramirez. [669] Eduardo Masato Iyoda and Fernando J. Von Zuben. Hybrid neural networks: An evolutionary approach with local search. Integrated Computer-Aided Engineering, 9(1):57–72, ? 2002. * http://iospress.metapress.com ga02aEMIyoda. [670] E. Ruppin. Evolutionary autonomous agents: A neuroscience perspective. Nature Review Neuroscience, 3(?):132–141, ? 2002. †[1904] ga02aERuppin. [671] Eva Volná. Evolutionary algorithms as a way to modular neural network structure. pages 206–210, 2002. ga02aEVolna. [672] F. Hakl, M. Hlaváček, and R. Kalous. Applications of neural networks optimised by genetic algorithms to Higgs boson search. In P. M. A. Sloot, C. J. Kenneth Tan, J. J. Dongarra, and A. G. Hoekstra, editors, Computational Science - ICCS 2002, International Conference, volume LNCS of 2331, pages 554–563, Amsterdam (The Netherlands), 21.-24. April 2002. Springer-Verlag Berlin Heidelberg. * www /Springer ga02aFHakl. [673] Güner Alpaydin, Günhan Dündar, and Sina Balkir. Evolution-based design of neural fuzzy networks using self-adapting genetic parameters. IEEE Transactions on Fuzzy Systems, 10(2):211–221, April 2002. ga02aGAlpaydin. [674] G. Armano, A. Murru, and F. Roli. Stock market prediction by a mixture of genetic-neural experts. International Journal of Pattern Recognition and Artificial Intelligence, 16(5):?, August 2002. †TKK/TKO ga02aGArmano. [675] Hugo de Garis and Michael Korkin. The CAM-Brain Machine (CBM): an FPGA-based hardware tool that evolves a 1000 neuron-net circuit module in seconds and updates a 75 million neuron artificial brain for real-time robot control. Neurocomputing, 42(1-4):35–68, January 2002. †www /Elsevier ga02aHdeGaris. Bibliography 97 [676] Henry Leung, Neville Dubash, and Nan Xie. Detection of small objects in clutter using a GA-PBF neural network. IEEE Transactions on Aerospace and Electronic systems, 38(1):98–118, January 2002. ga02aHLeung. [677] Janne Haverinen and Juha Röning. Adaptation through a stochastic evolutionary neuron migration process (SENMP). In Proceedings of the 2002 IEEE/RSJ International Conference on Intelligent Robots and Systems, volume ?, pages 1008–1013, Lausanne (Switzerland), ? 2002. IEEE, Piscataway, NJ. †[?] ga02aJanneHaverinen. [678] J. L. Marcelin. Genetic optimization of stiffened plates without the FE mesh support. International Journal for Numerical Methods in Engineering, 54(5):685–694, 20. June 2002. ga02aJLMarcelin. [679] José A. Gámez and José M. Puerta. Searching for the best elimination sequence in Bayesian networks by using ant colony optimization. Pattern Recognition Letters, 23(1-3):261–277, January 2002. ga02aJoseAGamez. [680] L. B. Jack and A. K. Nandi. Fault detection using support vector machines and artificial neural networks, augmented by genetic algorithms. Mechanical Systems and Signal Processing, 16(2-3):373–390, ? 2002. ga02aLBJack. [681] L. E. Hadden. Modeling interactions between filial imprinting and a predisposition using genetic algorithms and neural networks. Neurocomputing, 42(1-4):215–237, January 2002. †www /Elsevier ga02aLEHadden. [682] Limei Song, Xing-Hua Qu, and Shenghua Ye. Neural network and genetic algorithm technology in data mining of manufacturing quality information. In Belur V. Dasarathy, editor, Data Mining and Knowledge Discovery: Theory, Tools, and Technology IV, volume SPIE-4730, pages 60–68, ?, March 2002. The International Society for Optical Engineering. * www/SPIE Web ga02aLSong. [683] M. Anandarajan. Profiling Web usage in the workplace: A behavior-based artificial intelligence approach. Journal of Management Information Systems, 19(3):243–266, Summer 2002. * ISI ga02aMAnandarajan. [684] Man Mohan Rai. Towards a hybrid aerodynamic design procedure based on neural networks and evolutionary methods. In 20th AIAA Applied Aerodynamics Conference, Saint Louis, MO, 24.-26. June 2002. AIAA. AIAA Paper 2003-3143 * A02-31512 ga02aMMRai. [685] Michel Rixen, Jean-Marie Beckers, Alberto Alvarez, and Joaquim Tintore. Results on SSH neural network forecasting in the Mediterranean Sea. In Charles R. Bostater and Rosalia Santoleri, editors, Remote Sensing of the Ocean and Sea Ice 2001, volume SPIE-4544, pages 24–33, ?, January 2002. The International Society for Optical Engineering. * www/SPIE Web ga02aMRixen. [686] Michal Turčanı́k and Pavol Kaločay. The genetic algorithm optimization of the artificial neural network. pages 159–163, 2002. ga02aMTurcanik. [687] Nikolaos D. Doulamis, Anastasios D. Doulamis, Pavlos S. Georgilakis, Stefanos D. Kollias, and Nikos D. Hatziargyriou. A synergetic neural network-genetic scheme for optimal transformer construction. Integrated Computer-Aided Engineering, 9(1):37–56, ? 2002. * http://iospress.metapress.com ga02aNDDoulamis. [688] P.-J. Lu and T.-C. Hsu. Application of autoassociative neural network on gas-path sensor data validation. Journal of Propulsion and Power, 18(4):879–888, July 2002. * A02-35871 ga02aP-JLu. [689] P. K. Nanda, D. P. Muni, and P. Kanungo. Parallelized crowding scheme using a new interconnection model. In N. R. Pal and M. Sugeno, editors, Advances in Soft Computing - AFSS 2002, 2002 AFSS International Conference on Fuzzy Systems, volume LNAI of 2275, pages 436–443, Calcutta (India), 3.6. February 2002. Springer-Verlag Berlin Heidelberg. * www /Springer ga02aPKNanda. [690] Paul P. Adams and Kingsley J. A. Cox. Synaptic Darwinism and neocortical function. Neurocomputing, 42(1-4):197–214, January 2002. †www /Elsevier ga02aPRAdams. [691] Primož Potočnik and Igor Grabec. Nonlinear model predictive control of a cutting process. Neurocomputing, 43(1-4):107–126, March 2002. ga02aPrimozPotocnik. [692] Regis Duvigneau and Michel Visonneau. Hybrid genetic algorithms and neural networks for fast CFD-based design. In 9th AIAA/ISSMO Symposium and Exhibit on Multidisciplinary Analysis and Optimization, Atlanta, GA, 4.-6. September 2002. AIAA. AIAA Paper 2002-5465 * A02-40929 ga02aRDuvigneau. [693] Rosa Mariá Garcı́a-Gimeno, César Hervás-Martı́nez, and Maria Isabel de Silóniz. Improving artificial neural networks with a pruning methodology and genetic algorithms for their applications in microbial growth prediction in food. Journal of Food Microbiology, 72(1-2):19–30, 30. January 2002. †www /Elsevier ga02aRMGarcia-Gimeno. 98 Genetic algorithms and neural networks [694] Ramaswamy Palaniappan, Paramesran Raveendran, and Sigeru Omatu. VEP optimal channel selection using genetic algorithm for neural classification of alcoholics. IEEE Transactions on Neural Networks, 13(2):486–491, March 2002. ga02aRPalaniappan. [695] R. S. Sexton, R. A. Johnson, and M. A. Hignite. Predicting Internet/e-commerce use. Internet ResearchElectronic Networking Applications and Policy, 12(5):402–410, 2002. * ISI ga02aRSSexton. [696] Ruben E. Perez and Kamran Behdinan. Effective multi-mission aircraft conceptual design optimization using a hybrid multi-objective evolutionary method. In 9th AIAA/ISSMO Symposium and Exhibit on Multidisciplinary Analysis and Optimization, Atlanta, GA, 4.-6. September 2002. AIAA. AIAA Paper 2002-5464 * A02-40928 ga02aRubenEPerez. [697] Sunghwan Sohn and Cihan H. Dagli. Adaptable multiple neural networks using evolutionary computation. In Kevin L. Priddy, Paul E. Keller, and Peter J. Angeline, editors, Applications and Science of Computational Intelligence V, volume SPIE-4739, pages 141–149, ?, March 2002. The International Society for Optical Engineering. * www/SPIE Web ga02aSSohn. [698] Thomas Ragg. Bayesian learning and evolutionary parameter optimization. AI Communications, 15(1):61– 74, ? 2002. * www /Google ga02aTRagg. [699] Vladimir Olej. Prediction of gross domestic product development on the basis of neural networks, genetic and Eugenic algorithms. pages 153–158, 2002. ga02aVOlej. [700] William Leigh, Russell Purvis, and James M. Ragusa. Forecasting the NYSE composite index with technical analysis, pattern recognizer, neural network, and genetic algorithm: a case study in romantic decision support. Decision Support Systems, 32(?):361–377, ? 2002. ga02aWilliamLeigh. [701] Y. Frayman, B. F. Rolfe, and G. I. Webb. Improving on inverse model of sheet metal forming by neural network based regression. In ?, editor, Proceedings of DECTC2002, The 2002 ASME Computers and Information in Engineering Conference, pages 1–8, ?, ? 2002. ASME Press. ga02aYFrayman. [702] Yongyong He, Fulei Chu, and Binglin Zhong. A hierarchical evolutionary algorithm for constructing and training wavelet networks. Neural Computing & Applications, 10(4):357–366, ? 2002. * www /Springer ga02aYHe. [703] Yoshiaki Katada, Yutaka Yasuda, Kazuhiro Ohkura, and Kanji Ueda. Evolutionary dynamics on neural networks. pages 35–40, 2002. ga02aYoshiakiKatada. [704] Zikrija Avdagic and Samim Konjicija. Design of robot controller based on evolutionary algorithms and neural networks. In Proceedings of the 6th World Multiconference on Systemics, Cybernetics and Informatics, page ?, Orlando, FL, ? 2002. ? † ga02aZAvdagic. [705] Zümray Dokur, Mehmet Nadir Kurnaz, and Tamer Ölmez. Segmentation of ultrasound images by using quantizer neural network. In ?, editor, Proceedings of the 15th IEEE International Symposium on Computer-Based Medical Systems, pages 257–261, ?, 4.-7. June 2002. IEEE Computer Society, Piscataway, NJ. ga02aZDokur. [706] Zhan hong Xin and Hai jun Zhang. Neural network and genetic algorithms for topology optimization of the CCS7 network. International Transactions in Operational Research, 9(4):427–436, July 2002. ga02aZhan-hongXin. [707] Z. S. H. Chan, H. W. Ngam, A. B. Rad, and T. K. Ho. Alleviating ’overfitting‘ via genetically-regularised neural network. Electronics Letters, 38(15):809–810, 18. July 2002. ga02aZSHChan. [708] Christian Igel and Peter Stagge. Graph isomorphisms effect structure optimisation of neural networks. In ?, editor, International Joint Conference on Neural Networks 2002 (IJCNN), volume ?, page ?, ?, ? 2002. IEEE Press. ga02bChristianIgel. [709] H. K. Lam, K. F. Leung, S. H. Ling, F. H. F. Leung, and P. K. S. Tam. On interpretation of graffiti digits and commands for ebooks: neural fuzzy network and genetic algorithm approach. In Proceedings of the 2002 IEEE International Conference on Fuzzy Systems. FUZZ-IEEE’02, volume ?, pages 443–448, ?, 12.-17. May 2002. IEEE, Piscataway, NJ. ga02bHKLam. [710] Janne Haverinen and Juha Röning. A stochastic evolutionary neuron migration process with emerged Hebbian dynamics. In Artificial Life VIII: The 8th International Conference on the Simulation and Synthesis of Living Systems, volume ?, page ?, Sydney (Australia), ? 2002. ? †[?] ga02bJanneHaverinen. [711] Maurı́cio Ruv Lemes and Arnaldo Dal Pino Jr. Estudo do estado fundamental de aglomerados de silı́cio via redes neurais [Study of the ground-state geometry of silicon clusters through artificial neural networks. Quim. Nova, 25(4):539–543, ? 2002. (in Portuguese) ga02bMRLemes. Bibliography 99 [712] Terence Soule, Ying Yin Chen, and Richard B. Wells. Evolving a strongly recurrent neural network to simulate biological neurons. In Proceedings of the 2002 28th IEEE Annual Conference of the IECON 02, volume 4, pages 3191–3195, ?, ? 2002. IEEE, Piscataway, NJ. ga02bTerenceSoule. [713] Arthur K. Kordon, Guido F. Smits, Alex N. Kalos, and Elsa M. Jordaan. Chapter 3. robust soft sensor development using genetic programming. In Riccardo Leardi, editor, Nature-inspired Methods in Chemometrics and Artificial Neural Networks, pages 69–108. Elsevier, Amsterdam, 2003. †TKKpaa ga03aAKKordon. [714] B. Pichler, R. Lackner, and H. A. Mang. ack analysis of model parameters in geotechnical engineering by means of soft computing. International Journal for Numerical Methods in Engineering, 57(14):1943–1978, 14. August 2003. * TKKpaa ga03aBPichler. [715] Conrad Bessant and Edward Richards. Chapter 9. neural networks for the calibration of voltammetric data. In Riccardo Leardi, editor, Nature-inspired Methods in Chemometrics and Artificial Neural Networks, pages 257–280. Elsevier, Amsterdam, 2003. †TKKpaa ga03aCBessant. [716] Craig C. Ewert and Yakov Keselman. Evolving ANN for edge detection. In ?, editor, Proceedings of the DePaul CTI Research Symposium, page ?, ?, 8. November 2003. ? ga03aCCEwert ⇒ http://kinderspirit. org/yakovkeselman/Publications/ceyk2003cti.pdf. [717] Christian Igel and Martin Kreutz. Operator adaptation in evolutionary computation and its application to structure optimization of neural networks. Neurocomputing, 55(1-2):347–361, September 2003. †ISI ga03aCIgel. [718] Emanuel Falkenauer and Arnaud Marchand. Clustering microarray data with evolutionary algorithms. In Gary B. Fogel and David W. Corne, editors, Evolutionary Computation in Bioinformatics, pages 219–230. Morgan Kaufmann Publishers, New York, 2003. †TKKpaa ga03aEFalkenauer. [719] Gregory A. Holifield and Annie S. Wu. A genetic algorithm as learning method based on geometric representations. In ?, editor, Genetic and Evolutionary Computation - GECCO 2003, Proceedings, volume 2724 of Lecture Notes in Computer Science, pages 1588–1589, ?, ? 2003. Springer-Verlag, Heidelberg. ga03aGAHolifield. [720] G. Capi and K. Doya. Evolving recurrent neural controllers for sequential tasks: A parallel implementation. In Proceedings of the Congress on Evolutionary Computation (CEC-2003), volume 1, pages 514–519, ? 2003. †[1904] ga03aGCapi. [721] Hui-Yuan Fan and Jouni Lampinen. A trigonometric mutation operation to differential evolution. Journal of Global Optimization, 27(?):105–129, ? 2003. ga03aHui-YuanFan. [722] João A. Fabro and Lúcia V. R. Arruda. Fuzzy-neuro predictive control, tuned by genetic algorithms, applied to a fermentation process. In Proceedings of the 2003 IEEE International Symposium on Intelligent Control, pages 194–199, Houston, TX, 5.-8. October 2003. IEEE, Piscataway, NJ. ga03aJAFabro. [723] Joao Camargo Neto, George E. Meyer, David D. Jones, and Alvin J. Surkan. Adaptive image segmentation using a fuzzy neural network and genetic algorithm for weed detection. In ?, editor, Proceedings of the 2003 ASAE Annual Meeting, page paper number 033088, ?, ? 2003. ASABE. †ASABE ga03aJCNeto. [724] Jarmo Ilonen, Joni-Kristian Kämäräinen, and Jouni Lampinen. Differential evolution training algorithm for feed-forward neural networks. Neural Processing Letters, 17(1):93–105, ? 2003. ga03aJIlonen. [725] Leandro Nunes de Castro, Fernando J. Von Zuben, and Getúlio A de Deus Jr. The construction of a Boolean competitive neural network using ideas from immunology. Neurocomputing, 50(1):51–85, January 2003. †TKK /TKO ga03aLNdeCastro. [726] Mauro Annunziato, Ilaria Bertini, A. Pannicelli, and Stefano Pizzuti. Evolutionary feed-forward neural networks for traffic prediction. In G. Bugeda et al, editor, Proceedings of the International Congress on Evolutionary Methods for Design, Optimization and Control with Applications to Industrial Problems, EUROGEN 2003, pages –, ?, ? 2003. CIMNE, Barcelona. ga03aMAnnunziato. [727] Marylyn D. Ritchie, Bill C. White, Joel S. Parker, Lance W. Hahn, and Jason H. Moore. Optimization of neural network architecture using genetic programming improves detection and modeling of gene-gene interactions in studies of human diseases. BMC Bioinformatics, 4(?):28–42, 7. July 2003. ga03aMDRitchie. [728] P. S. Satsangi, D. S. Mishra, S. K. Gaur, and B. K. Singh. Systems dynamics modelling, simulation and optimization of integrated urban systems: a soft computing approach. Kybernetes, 32(5-6):808–817, 2003. * ISI ga03aPSSatsangi. [729] Reid Porter, Neal Harvey, Simon Perkins, James Theiler, Steven Brumby, Jeffrey Bloch, Maya Gokhale, and John Szymanski. Optimizing digital hardware perceptrons for mult-spectral image classification. Journal of Mathematical Imaging and Vision, 19(2):133–150, 2003. ga03aReidPorter. 100 Genetic algorithms and neural networks [730] Reinhard Meusinger and Uwe Himmelreich. Chapter 10. neural networks and genetic algorithms applications in nuclear magnetic resonance (NMR) spectroscopy. In Riccardo Leardi, editor, Nature-inspired Methods in Chemometrics and Artificial Neural Networks, pages 281–322. Elsevier, Amsterdam, 2003. †TKKpaa ga03aRMeusinger. [731] Shu-Chen Cheng and Yueh-Min Huang. A novel approach to diagnose diabetes based on the fractal characteristics of retinal images. IEEE Transactions on Information Technology in Biomedicine, 7(3):163– 170, September 2003. ga03aShu-ChenCheng. [732] Shun Heng Chan. Novel mutation operators and their application to regularization of artificial neural networks. PhD thesis, Hong Kong Polytechnic University, 2003. * www /UMI ga03aShunHengChan. [733] T. Morimoto, K. Tu, K. Hatou, and Y. Hashimoto. Dynamic optimization using neural networks and genetic algorithms for tomato cool storage to minimize water loss. Transactions of the ASAE, 46(4):1151– 1159, ? 2003. †www /CAT.INIST ga03aTMorimoto. [734] Vikram Aedula and Cihan Dagli. Collective behavior in robots using evolutionary neural networks. In Ulrich Rückert and Joaquin Sitte, editors, Proceedings of the 2nd International Symposium on Autonomous Minirobots for Research and Edutainment (AMiRE), pages 63–72, Brisbane, QLD (Australia), 18.-20. February 2003. Queensland University of Technology, CITI. ga03aVikramAedula. [735] Weizhen Lu, H. Y. Fan, and S. M. Lo. Application of evolutionary neural network method in predicting pollutant levels in downtown area of Hong Kong. NeuroComputing, 51(?):387–400, ? 2003. †Wenjian Wang ga03aWeizhenLu. [736] Y. Y. Yang, D. A. Linkens, and M. Mahfouf. Genetic algorithms and hybrid neural network modelling for aluminium stress-strain prediction. Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, 217(1):7–21, ? 2003. †www /Google ga03aYYYang. [737] Zikrija Avdagic. Vještačka inteligencija & fuzzy-neuro-genetika. Grafoart, Sarajevo (B&H), ? 2003. †[758] ga03aZAvdagic. [738] Gary B. Fogel, Kumar Chellapilla, and David B. Fogel. Identification of coding regions in DNA sequences using evolved neural networks. In Gary B. Fogel and David W. Corne, editors, Evolutionary Computation in Bioinformatics, pages 193–218. Morgan Kaufmann Publishers, New York, 2003. †TKKpaa ga03bGBFogel. [739] Jun an Yang, Hui Peng, and Zhenquan Zhuang. Research of nonlinear blind source separation algorithm based on quantum evolutionary neural network. In Proceedings of the 2003 IEEE International Conference on Machine Learning and Cybernetics, volume 2, pages 835–840, Xi’an (China), 2.-5. November 2003. IEEE, Piscataway, NJ. ga03bJun-anYang. [740] Alex van Eck Conradie. A Neurocontroll Paradigm for Intelligent Process Control using Evolutionary Reinforcement Learning. PhD thesis, University of Stellenbosch, 2004. * Google ga04aAlexvanEckConradie. [741] A. S. Cofiño, J. M. Gutiérrez, and M. L. Ivanissevich. Evolving modular networks with genetic algorithms: application to nonlinear time series. Expert Systems, 21(4):208–216, September 2004. ga04aASCofino. [742] B. Curry and P. H. Morgan. Evaluating Kohonen’s learning rule: An approach through genetic algorithms. European Journal of Operational Research, 154(1):191–205, 1. April 2004. * www /SceinceDirect ga04aBCurry. [743] Bahram Hemmateenejad and Mojtaba Shamsipur. Quantitative structure-electrochemistry relationship study of some organic compounds using PC-ANN and PCR. Internet Electronic Journal of Molecular Design, 3(6):316–334, June 2004. ga04aBHemmateenejad. [744] Christian Mayr and René Schüffny. Noise shaping in spiking neural nets - network design issues. In Circuits and Systems, 2004. MWSCAS ’04. The 2004 47th Midwest Symposium on, volume 2, pages II–401–II–404, ?, 25.-28. July 2004. IEEE, Piscataway, NJ. ga04aCMayr. [745] Enrique Alba and J. Francisco Chicano. Training neural networks with GA hybrid algorithms. In Kalyanmoy Deb et al, editor, Genetic and Evolutionary Computation - GECCO 2004, volume 3102 of Lecture Notes in Computer Science, pages 852–863, Seattle, WA, 26.-30. June 2004. Springer-Verlag, Berlin. ga04aEAlba. [746] G. Capi and K. Doya. Evolution of neural architecture fitting environmental dynamics. Adaptive Behavior, 13(?):53–66, ? 2004. †[1904] ga04aGCapi. [747] Harri Niska, Teri Hiltunen, Ari Karppinen, Juhani Ruuskanen, and Mikko Kolehmainen. Evolving the neural network model for forecasting air pollution time series. Engineering Applications of Artificial Intelligence, 17(?):159–167, ? 2004. ga04aHarriNiska. Bibliography 101 [748] Janne Haverinen. Adaptation Through Stochastic Evolutionary Neuron Migration Process. PhD thesis, University of Oulu, Department of Electrical and Information Engineering, 2004. ga04aHaverinen. [749] Haralambos Sarimveis, Alex Alexandridis, Stefanos Mazarakis, and George Bafas. A new algorithm for developing dynamic radial basis function neural network models based on genetic algorithms. Computers & Chemical Engineering, 28(1-2):209–217, 15. January 2004. * www /ScienceDirect ga04aHSarimveis. [750] Juho Kontio. Neuroevolution based artificial bandwidth expansion of telephone band speech [Neuroevoluutiopohjainen puhelinpuheen taajuuskaistan keinotekoinen laajentaminen]. Master’s thesis, Helsinki University of Technology, 2004. †www /TKK ga04aJuhoKontio. [751] Michael John Watts. Evolving Connectionist Systems — Characterisation, Simplification, Formalisation, Explanation and Optimisation. PhD thesis, University of Otago, 2004. ga04aMJWatts ⇒ http://otago. ourarchive.ac.nz/bitstream/handle/10523/1489/MikeWatts-thesis.pdf. [752] Ronald Setia, Gary S. May, Venky Sundaram, Rao R. Tummala, and Hyoung Ho Roh. Sensitivity analysis and optimization of excimer laser ablation for microvia formation using neural network and genetic algorithms. In Proceedings of the 2004 IEEE/CPMT/SEMI 29th International Symposium on Electronics Manufacturing Symposium, pages 131–139, ?, 14.-15. July 2004. IEEE, Piscataway, NJ. ga04aRSetia. [753] Thomas P. Knight. MARIA: A Multi-Layered Unsupervised Machine Learning Algorithm Based on the Vertebrate Immune System. PhD thesis, The University of Kent at Canterbury, 2004. ga04aTPKnight ⇒ http://www-users.cs.york.ac.uk/jtimmis/thesis/knight.pdf. [754] Bahram Hemmateenejad. Optimal QSAR analysis of the carcinogenic activity of drugs by correlation ranking and genetic algorithm-based PCR. Journal of Chemometrics, 18(?):475–485, ? 2004. ga04bBHemmateenejad. [755] Carlos Andrés Peña-Reyes. Coevolutionary fuzzy modeling. In Coevolutionary fuzzy modeling, volume 3204 of Lecture Notes in Computer Science. Springer-Verlag, Heidelberg, 2004. †www /ISI ga04bCAPena-Reyes. [756] Ronald Setia and Gary S. May. Modeling and optimization of via formation in dielectrics by laser ablation using neural networks and genetic algorithms. IEEE Transactions on Electronics Packaging Manufacturing, 27(2):133–144, April 2004. ga04bRSetia. [757] Adrian Costas and Iulian Nastac. Assessing the predictive performance of artificial neural networkbased classifiers based on different data preprocessing methods, distributions and training mechanisms. Intelligent Systems in Accounting, Finance & Management, 13(4):217–250, ? 2005. †www /Google ga05aAdrianCostas ⇒ http://www3.interscience.wiley.com/journal/112750587/abstract?CRETRY= 1&SRETRY=0. [758] Bakir Lacevic, Samim Konjicija, and Zikrija Avdagic. Great selection pressure genetic algorithm with adaptive operators for adjusting the weights of neural controller. In Proceedings 2005 IEEE International Symposium on Computational Intelligence in Robotics and Automation (CIRA2005), page ?, Espoo (Finland), 27.-30.June 2005. IEEE, Piscataway, NJ. ga05aBLacevic. [759] Christian Mayr and René Schüffny. Applying spiking neural nets to noise shaping. IEICE Transactions on Information and Systems, E88-D(?):1885–1892, ? 2005. †www /Google ga05aCMayr. [760] Damergi Emir, Benrebaa Abdellatif, and Bouallegue Ammar. A genetic algorithm based resources optimization methodology for implementing artificial neural networks on FPGAs. In Proceedings of the 12th IEEE International Conference on Electronics, Circuits and Systems ICECS’05, pages 1–4, ?, 11.-14. December 2005. IEEE, Piscataway, NJ. ga05aDEmir. [761] Harri Niska, Minna Rantamäki, Teri Hiltunen, Ari Karppinen, Jaakko Kukkonen, Juhani Ruuskanen, and Mikko Kolehmainen. Evaluation of an integrated modelling system containing a multi-layer perceptron model and the numerical weather prediction model HIRLAM for the forecasting of urban airborne pollutant concentrations. Atmospheric Environment, 39(?):6524–6536, ? 2005. ga05aHarriNiska. [762] Hiroshi Kawano. Application of single neuron model to motion planning and control of under-actuated robot by MDP frame work. In Proceedings 2005 IEEE International Symposium on Computational Intelligence in Robotics and Automation (CIRA2005), page ?, Espoo (Finland), 27.-30.June 2005. IEEE, Piscataway, NJ. ga05aHiroshiKawano. [763] Jacek Frankowski. Neural network with hybrid learning strategy for financial time series forecasting. In Yuping Wang, Yiu ming Cheung, and Hailin Liu, editors, Advances in Computational Intelligence and Security, Proceedings of the Workshop of 2005 International Conference on Computational Intelligence and Security, pages 72–76, Xian (China), 15. December 2005. Xidian University Press. ga05aJFrankowski. 102 Genetic algorithms and neural networks [764] Lipo Wang, Lei Zhou, and Wen Liu. FPGA segmented channel routing using genetic algorithms. In Proceedings of the 2005 IEEE Congress on Evolutionary Computation, volume 3, pages 2161–2165, ?, 2.-5. September 2005. IEEE, Piscataway, NJ. ga05aLipoWang. [765] Naoyuki Kubota and Hironobu Sasaki. Genetic algorithm for a fuzzy spiking neural network of a mobile robot. In Proceedings 2005 IEEE International Symposium on Computational Intelligence in Robotics and Automation (CIRA2005), page ?, Espoo (Finland), 27.-30.June 2005. IEEE, Piscataway, NJ. ga05aNaoyukiKubota. [766] Paulito P. Palmes, Taichi Hayasaka, and Shiro Usui. Mutation-based genetic neural network. IEEE Transactions on Neural Networks, 16(3):587–600, May 2005. ga05aPPPalmes. [767] Rodrigo Calvo, Mauricio Figueiredo, and Eric Aislan Antonelo. Evolutionary fuzzy system for architecture control in a constructive neural network. In Proceedings 2005 IEEE International Symposium on Computational Intelligence in Robotics and Automation (CIRA2005), page ?, Espoo (Finland), 27.-30.June 2005. IEEE, Piscataway, NJ. ga05aRCalvo. [768] Vivechana Dixit, Jagdish C. Tewari, Byoung-Kwan Cho, and Joseph M. K. Irudayaraj. Identification and quantification of industrial grade glycerol adulteration in red wine with Fourier transform infrared spectroscopy using chemometrics and artificial neural networks. Applied Spectroscopy, 59(12):288A–308A, December 2005. * Google ga05aVivechanaDixit ⇒ http://www.ingentaconnect.com/content/sas/sas/2005/00000059/00000012/art00022?token= 00571da6b67a5e83ff25f573d257025707b2379462a403442552b657c4e7547543c7e386f642f466fa48803. [769] Damergi Emir, Benrebaa Abdellatif, and Bouallegue Ammar. Efficient finite word length determination for neural networks implementation. In Proceedings of the International Conference on omputational Intelligence for Modelling, Control and Automation, and International Conference on Intelligent Agents, Web Technologies and Internet Commerce (CIMCA-IAWTIC’05), volume 2, pages 31–35, ?, 28.-30. November 2005. IEEE, Piscataway, NJ. ga05bDEmir. [770] A. Flores-Mendez and Eduardo Gómez-Ramı́rez. Forecasting time series with a new architecture for polynomial artificial neural networks. In Proceedings of the 2006 International Joint Conference on Neural Networks, volume ?, pages 4357–4362, Vancouver, BC, 16.-21. July 2006. IEEE, Piscataway, NJ. ga06aAFlores-Mendez. [771] Eduardo Gomez-Ramirez, Giovanni Egidio Pazienza, and Xavier Vilasis-Cardona. Polynomial discrete time cellular neural networks to solve the XOR problem. In Proceedings of the 10th International Workshop on Cellular Neural Networks and Their Applications (CNNA’06), pages 1–6, ?, ? 2006. IEEE, Piscataway, NJ. ga06aEGomez-Ramirez. [772] J. Maher, B. McGinley, P. Rocke, and F. Morgan. Intrinsic hardware evaluation of neural networks in reconfigurable analogue and digital devices. In Proceedings of the 14th Annual IEEE Symposium on Field-Programmable Custom Computing Machines, FCCM’06, pages 321–322, ?, 24.-26. April 2006. IEEE, Piscataway, NJ. ga06aJMaher. [773] Mauro Annunziato, Ilaria Bertini, R. Iannone, and Stefano Pizzuti. Evolving feed-forward neural networks through evolutionary mutation parameters. In ?, editor, Proceedings, Intelligent Data Engineering and Automated Learning, IDEAL 2006, volume 4224 of Lecture Notes in Computer Science, pages 554–561, ?, ? 2006. Springer-Verlag, Heidelberg. †www /ISI Springer ga06aMAnnunziato. [774] Mario Ventresca and Beatrice Ombuki. Search space analysis of recurrent spiking and continuous-time neural networks. In Proceedings of the International Joint Conference on Neural Networks (IJCNN’06), volume ?, pages 4514–4521, ?, ? 2006. IEEE, Piscataway, NJ. ga06aMarioVentresca. [775] Qingwu Fan, Pu Wang, Lianbao Zhang, and Jun Li. The research of expert system of laser quenching based on genetic-neural network. In Proceedings of the 6th World Congress on Intelligent Control and Automation, volume ?, pages 7969–7972, Dalian (China), 21-23. June 2006. IEEE, Piscataway, NJ. ga06aQingwuFan. [776] Ramesh Gautam, Suranjan Panigrahi, and David Franzen. Neural network optimization of remotely sensed maize leaf nitrogen with a genetic algorithm and linear programming using five performance parameters. Biosystems Engineering, 95(3):359–370, ? 2006. ga06aRameshGautam. [777] Yuan-Peng Wang. Optimizing the Radial Basis Function Neural Network by Heuristic Algorithms. PhD thesis, University in Taiwan, 2006. * Google ga06aYuan-PengWang ⇒ http://ndltd.ncl.edu.tw/cgi-bin/ gs32/gsweb.cgi/ccd=unDPW2/record?r1=46&h1=5. [778] Enrique Alba, J. Francisco Chicano, Francisco Luna, Gabriel Luque, and Antonio J. Nebro. Ch. 26 advanced evolutionary algorithms for training neural networks. In Stephan Olariu and Albert Y. Zomaya, editors, Handbook of Bioinspired Algorithms and Applications, pages –, ?, ? 2006. Chapman & Hall / CRC. †www / Google books ga06bEnriqueAlba. Bibliography 103 [779] Bishweswar Sahoo and Damodar Maity. Damage assessment of structures using hybrid neuro-genetic algorithm. Applied Soft Computing, 7(1):89–104, January 2007. * www /google ga07aBSahoo. [780] Eduardo Gómez-Ramı́rez, K. Najim, and E. Ikonen. Forecasting time series with a new architecture for polynomial artificial neural networks. Applied Soft Computing, 7(4):1209–1216, August 2007. ga07aEGomez-Ramirez. [781] Frieke M. B. Van Coillie, Lieven P. C. Verbeke, and Robert R. De Wulf. Feature selection by genetic algorithms in object-based classification of IKONOS imagery for forest mapping in Flanders, Belgium. Remote Sensing of Environment, 110(?):476–487, ? 2007. ga07aFMBVanCoillie. [782] Mauro Annunziato, Ilaria Bertini, Matteo De Felice, and Stefano Pizzuti. Evolving complex neural networks. In ?, editor, Proceedings of the AI*IA 2007, pages –, Rome (Italy), September 2007. ? ga07aMAnnunziato ⇒ http://guanchitos.casaccia.enea.it/stefano/eng/pub en.html. [783] Mohamad Awad, Kacem Chehdi, and Ahmad Nasri. Multicomponent image segmentation using a genetic algorithm and artificial neural network. IEEE Geoscience and Remote Sensing Letters, 4(4):571–575, October 2007. ga07aMAwad. [784] M. Hamedi and S. A. Mansourzadeh. Automotive body welding optimization using neuro-genetic algorithms. In ?, editor, Proceedings of the 18th IASTED International Conference on Modeling and Simulation, pages 289–294, Montreal, Quebec, 30. May-1. June 2007. IASTED. ga07aMHamedi. [785] M. S. Alajmi and F. Alfares. Prediction of cutting forces in turning process using de-neural networks. In V. Devedžic, editor, Artificial Intelligence and Applications AIA2007, pages 549–173, Innsbruck (Austria), 12.-14. February 2007. ACTA Press. †ACTA Press ga07aMSAlajmi. [786] Sammy Siu, Sheng-Sung Yang, Chien-Min Lee, and Chia-Lu Ho. Improving the back-propagation algorithm using evolutionary strategy. IEEE Transactions on Circuits and Systems, II: Express Briefs, 54(2):171–175, February 2007. ga07aSammySiu ⇒ http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=04100879. [787] Stanley Gotshall, Kathy Browder, Jessica Sampson, Terence Soule, and Richard Wells. Stochastic optimization of a biologically plausible spino-neuromuscular system model, a comparison with human subjects. Genetic Programming and Evolvable Machines, 8(4):355–380, December 2007. ga07aSGotshall ⇒ http://www.springerlink.com/content/x071780j42017846/. [788] Wenjuan Liu, Qiang Liu, Feng Ruan, Zhiyong Liang, and Hongyang Qiu. Springback prediction for sheet metal forming based on GA-ANN technology. Journal of Materials Processing Technology, 187-188(?):227– 231, ? 2007. ga07aWenjuanLiu. [789] Yueju Xue, Shuguang Liu, Yueming Hu, Jingfeng Yang, and Qiang Chen. Genetic algorithm based adaptive neural network ensemble and its application in predicting carbon flux. In Proceedings of 3rd International Conference on Natural Computation (ICNC 2007), volume ?, page ?, ?, ? 2007. IEEE, Piscataway, NJ. ga07aYuejuXue. [790] Eduardo Gómez-Ramı́rez and Giovanni Egidio Pazienza. The game of life using polynomial discrete time cellular neural networks. In ?, editor, Analysis and Design of Intelligent Systems using Soft Computing Techniques, volume 41 of Advances in Soft Computing, pages 719–726, ?, ? 2007. Springer-Verlag, Heidelberg. †www /Springer ga07bEGomez-Ramirez. [791] Jouni Tiilikainen, V. Bosund, M. Mattila, T. Hakkarainen, J. Sormunen, and H. Lipsanen. Fitness function and nonunique solutions in x-ray reflectivity curve fitting: crosserror between surface roughness and mass density. Journal of Physics D-Applied Physics, 40(14):4259–4263, 21. July 2007. GA07bJouniTiilikainen. [792] Mauro Annunziato, Ilaria Bertini, Matteo De Felice, and Stefano Pizzuti. Reti neurali evolutive con topologia a rete complessa. In ?, editor, Proceedings of the WIVACE 2007, pages –, Sampieri (Italy), September 2007. ? ga07bMAnnunziato ⇒ http://guanchitos.casaccia.enea.it/stefano/ita/index. html. [793] Byungwhan Kim and Min Ji Kwon. Optimization of principal-component-analysis-applied in situ spectroscopy data using neural networks and genetic algorithms. Applied Spectroscopy, 62(1):73–75, January 2008. * Google ga08aByungwhanKim ⇒ http://www.ncbi.nlm.nih.gov/pubmed/18. [794] F. Ceravolo, B. Di Pietra, S. Pizzuti, and G. Puglisi. Neural models for ambient temperature modeling. In Proceedings of the 2008 CIMSA IEEE International Conference on Computational Intelligence for Measurement Systems and Applications, pages –, Istanbul (Turkey), 14.-16. July 2008. IEEE, Piscataway, NJ. ga08aFCeravolo. [795] Hualiang Zhuang, Kay-Soon Low, and Wei-Yun Yau. A multiplier-less GA optimized pulsed neural network for satellite image analysis using a FPGA. In Proceedings of the 3rd IEEE Conference on Industrial Electronics and Applications ICIEA 2008, pages 302–307, ?, 3.-5. June 2008. IEEE, Piscataway, NJ. ga08aHualiangZhuang. 104 Genetic algorithms and neural networks [796] Junlong Fang, Changli Zhang, and Shuwen Wang. Application of genetic algorithm (GA) trained artificial neural network to identify tomatoes with physiological diseases. In ?, editor, Computer and Computer Technologies in Agriculture, Vol. II, volume 259 of IFIP, pages 1103–1111, ?, ? 2008. Springer-Verlag, Heidelberg. †www /Springer ga08aJunlongFang. [797] Nikolaos E. Mitrakis, Charalampos A. Topaloglou, Thomas K. Alexandridis, and John B. Theocharis. Decision fusion of GA self-organizing neuro-fuzzy multilayered classifiers for land cover classification using textural and spectral features. IEEE Transactions on Geoscience and Remote Sensing, 46(7):2137–2152, July 2008. ga08aNEMitrakis. [798] Yutana Jewajinda. An adaptive hardware classifier in FPGA based-on a cellular compact genetic algorithm and block-based neural network. In Proceedings of the International Symposium on Communications and Information Technologies, ISCIT’08, pages 658–663, ?, 21.-23. October 2008. IEEE, Piscataway, NJ. ga08aYJewajinda ⇒ http://ieeexplore.ieee.org/xpls/abs all.jsp?arnumber=4700275. [799] András Fülöp and Jenö Hancsók. Comparison of calibration models based on near infrared spectroscopy data for the determination of plant oil properties. In Proceedings of the The Ninth International Conference on Chemical & Process Engineering ICheaP-9, volume ?, page ?, Rome (Italy), 10.-13. May 2009. The Italian Association of Chemical Engineering. ga09aAndrasFulop. [800] Brigitte Röthlein. ga09aBRothlein. Catching worms with quanta. Pictures of the Future, ?(?):54–56, Spring 2009. [801] Eduardo Gomez-Ramirez, Enrique Haro Sedeño, and Giovanni Egidio Pazienza. Discovering universal polynomial cellular neural networks through genetic algorithms. In ?, editor, Bio-inspired Hybrid Intelligent Systems for Image Analysis and Pattern Recognition, volume 256 of Studies in Computational Intelligence, pages 165–175, ?, ? 2009. Springer-Verlag. †www /Springer ga09aEGomez-Ramirez. [802] F. Morgan, S. Cawley, B. McGinley, S. Pande, L. J. McDaid, B. Glackin, J. Maher, and J. Harkin. Exploring the evolution of NoC-based spiking neural networks on FPGAs. In Proceedings of the 2009 IEEE International Conference on Field-Programmable Technology, FPT 2009, pages 300–303, Sydney, NSW, 9.-11. December 2009. IEEE, Piscataway, NJ. †www /IEEE ga09aFMorgan ⇒ http://ieeexplore.ieee. org/xpls/abs all.jsp?arnumber=5377663&tag=1. [803] Herry Suhardiyanto, Chusnul Arif, and Budi I. Setiawan. Optimization of EC values of nutrient solution for tomato fruit quality in hydroponics system using artificial neural network and genetic algorithms. ITB Journal of Science, 41(1):38–49, ? 2009. ga09aHSuhardiyanto. [804] Myriam Regattieri Delgado, Elaine Yassue Nagai, and Lucia Valéria Ramos de Arruda. A neurocoevolutionary genetic fuzzy system to design soft sensors. Soft Computing, 13(?):481–495, ? 2009. * Springer ga09aMRDelgado. [805] Wang Rong-Ji, Li Xin-hua, Wu Qing-ding, and Wang Lingling. Optimizing process parameters for selective laser sintering based on neural network and genetic algorithm. International Journal of Advanced Manufacturing Technology, 42(?):1035–1042, ? 2009. ga09aWangRong-Ji. [806] X. Du, J. Cheng, and J. Song. Improved prediction of protein binding sites from sequences using genetic algorithm. Protein Journal, ?(?):?, ? 2009. (in press) †PubMed ga09aXDu. [807] Yongxin Li, Yuanqian Li, Bo Zheng, Lingli Qu, and Can Li. Determination of foodborne pathogenic bacteria by multiplex PCR-microchip capillary electrophosesis with genetic algorithm-support vector regression optimization. Analytica Chimica Acta, 643(?):100–107, ? 2009. ga09aYongxinLi. [808] Sarawat Anam, Md. Shohidul Islam, M.A. Kashem, M.N. Islam, M.R. Islam, and M.S. Islam. Face recognition using genetic algorithm and back propagation neural network. In ?, editor, Proceedings of the International MultiConference of Engineers and Computer Scientists 2009 IMECS 2009, volume I, page ?, Hong Kong, 18.-20. March 2009. ? ga09SAnam ⇒ http://www.iaeng.org/publication/IMECS2009/ IMECS2009 pp811-814.pdf. [809] Adel Mellit, Soteris A. Karlogirou, and Mahmoud Drif. Application of neural networks and genetic algorithms for sizing of photovoltaic system. Renewable Energy, 35(12):2881– 2893, December 2010. ga10aAdelMellit ⇒ http://www.sciencedirect.com/science? ob= ArticleURL& udi=B6V4S-5045DND-1& user=8758044& coverDate=12%2F31%2F2010& rdoc=1& fmt= high& orig=search& sort=d& docanchor=&view=c& acct=C000109213& version=1& urlVersion= 0& userid=8758044&md5=702f813db61cce2dcbec91bb64f5e6ad. [810] Yutana Jewajinda and Prabhas Chongstitvatana. FPGA-based online-learning using parallel genetic algorithm and neural network for ECG signal classification. In Proceedings of the 2010 International Conference on : Electrical Engineering/Electronics Computer Telecommunications and Information Technology Bibliography 105 (ECTI-CON), pages 1050–1054, Chaing Mai, 19.-21. May 2010. IEEE, Piscataway, NJ. ga10aYJewajinda ⇒ http://ieeexplore.ieee.org/xpls/abs all.jsp?arnumber=5491636. [811] Hamid Mehmood and Nitin K. Tripathi. Optimizing artificial neural network-based indoor positioning system using genetic algorithm. International Journal of Digital Earth, ?(?):?, ? 2011. †Google ga11aHamidMehmood ⇒ http://www.tandfonline.com/doi/pdf/10.1080/17538947.2011.606337. [812] David Schafer, Larry Escherman, and Richard Karuana. Artificial neural network, 1991. (JP patent no. 3010366. Issued January 17 1991) * fi.espacenet.com ga91aDSchafer. [813] Alan V. Scherf and Lawrence D. Voelz. Training neural networks with genetic algorithms for target detection. In Dennis W. Ruck, editor, Science of Artificial Neural Networks, volume SPIE-1710, pages 734– 741, ?, July 1992. The International Society for Optical Engineering. * www/SPIE Web ga92aAVScherf. [814] Jan J. Mulawka. Recent progress in neural networks. In Andrej Sowinski, J. Grzybowski, Witold T. Kucharski, and Ryszard S. Romaniuk, editors, International Conference of Microelectronics: Microelectronics ’92, volume SPIE-1783, pages 2–12, ?, August 1992. The International Society for Optical Engineering. * www/SPIE Web ga92aJJMulawka. [815] Lei Xu and Stan Klasa. Recent advances on techniques and theories of feedforward networks with supervised learning. In Dennis W. Ruck, editor, Science of Artificial Neural Networks, volume SPIE-1710, pages 317–328, ?, July 1992. The International Society for Optical Engineering. * www/SPIE Web ga92aLXu. [816] Patrick E. Dessert. Anomaly detection in data using neural networks with natural selection. In Dennis W. Ruck, editor, Science of Artificial Neural Networks, volume SPIE-1710, pages 725–733, ?, July 1992. The International Society for Optical Engineering. * www/SPIE Web ga92aPEDessert. [817] Hideyuki Takagi. Fusion techniques of fuzzy systems and neural networks, and fuzzy systems and genetic algorithms. In Bruno Bosacchi and James C. Bezdek, editors, Applications of Fuzzy Logic Technology, volume SPIE-2061, pages 402–413, ?, December 1993. The International Society for Optical Engineering. * www/SPIE Web ga93aHTakagi. [818] Jochen Heistermann. Hybrid learning process for neural networks, e.g. for pattern recognition in speech processing - uses combination of stochastic and deterministic processes for optimizing system, 1993. (DE patent no. 4138053. Issued May 27 1993) * fi.espacenet.com ga93aJHeistermann. [819] John R. McDonnel and Donald E. Waagen. Evolving recurrent perceptrons. In Dennis W. Ruck, editor, Science of Artificial Neural Networks II, volume SPIE-1966, pages 350–361, ?, August 1993. The International Society for Optical Engineering. * www/SPIE Web ga93aJRMcDonnel. [820] Salah Darenfed. Genetic connectionism for computer tomographic reconstructions. In Raj S. Acharya and Dmitry B. Goldgof, editors, Biomedical Image Processing and Biomedical Visualization, volume SPIE1905, pages 987–996, ?, July 1993. The International Society for Optical Engineering. * www/SPIE Web ga93aSDarenfed. [821] Toru Fujii. Method and device for learning neural network, 1993. (JP patent no. 5143757. Issued June 11 1993) * fi.espacenet.com ga93aTFujii. [822] A. Conway. Echoed time series predictions neural networks and genetic algorithms. Vistas in Astronomy, 38(3):351, ? 1994. †NASA ADS ga94aAConway. [823] Takeshi Agui, T. Kakuyama, Hiroshi Nagahashi, and Tomoharu Nagao. A study on learning of neural networks using a genetic algorithm. J. Inst. Image Electron. Eng. Jpn. (Japan), 23(2):96–101, April 1994. * EEA 96005/94 ga94aAgui. [824] Peter J. Angeline and Jordan B. Pollack. Evolving neural networks. In Sebald and Fogel [1905], page ? †conf.prog ga94aAngeline. [825] Alan Scott Austin. Evolution of neural networks by implicit specification. In Sebald and Fogel [1905], page ? †conf.prog ga94aAustin. [826] Samy Bengio, Yoshua Bengio, and Jocelyn Cloutier. Genetic programming for the search of a new learning rule for neural networks. In ICEC’94 [1906], pages 324–327. ga94aBengio. [827] Joachim Born, Ivan Santibáñez-Koref, and Hans-Michael Voigt. Designing neural networks by adaptively building blocks in cascades. In Davidor et al. [1907], pages 472–481. †Born ga94aBorn. [828] Marko V. Borst. Local structure optimization in evolutionary generated neural network architectures. Master’s thesis, Leiden University, 1994. †[977] ga94aBorst. [829] Jürgen Branke, Udo Kohlmorgen, and Hartmut Schmeck. A distributed genetic algorithm improving the generalization behaviour of neural networks. Forschungsberichte 311, Universität Karlsruhe, Institut AIFB, 1994. ga94aBranke. 106 Genetic algorithms and neural networks [830] Heinrich Braun and Peter Zagorski. ENZO-M - a hybrid approach for optimizing neural networks by evolution and learning. In Davidor et al. [1907], page ? †conf. prog. ga94aBraun. [831] Byoung-Tak Zhang and Heinz Mühlenbein. Genetic breeding of novel neural architectures. In EUFIT’94 [1908], pages 1265–1269. ga94aBTZhang. [832] James J. Buckley, P. Krishnamraju, Kevin D. Reilly, and Yoichi Hayashi. Genetic learning algorithms for fuzzy neural nets. In Proceedings of ICCI94/Fuzzy Systems, pages –, Orlando, FL, 26. June - 2. July 1994. IEEE, New York, NY. ga94aBuckley. [833] H. Chen. Machine learning approach to document retrieval: An overview and an experiment. In Proceedings of the 27th Hawaii International Conference on Systems Sciences (HICSS-27), volume 3, pages 631–640, Wailea, HI, 4.-7. January 1994. IEEE Computer Society Press, Los Alamitos, CA. * EI M142628/94 ga94aChen. [834] David T. Cliff. Neuroethology, computational. Technical Report Report CSRP338, University of Sussex, School of Cognitive and Computing Science, 1994. (also as [983]; ftp://ftp.cogs.susx.ac.uk/pub/ reports/csrp/csrp338ps.Z) ga94aCliff. [835] J. E. Cooling and B. Korousic-Seljak. Task scheduling – using neural networks within hardware coprocessors. In Proceedings of the 7th Mediterranean Electrotechnical Conference (MELECON94), volume 1, pages 317–320, Antalya (Turkey), 12.-14. April 1994. IEEE, New York. †EI M048014/95 ga94aCooling. [836] Louis E. Coporaletti, Robert E. Dorey, John D. Johnson, and William A. Powell. Decision support system for in-sample simultaneous equation systems forecasting using artificial neural systems. Decis Support Syst, 11(5):481–495, 1994. †EI M 120226 ga94aCoporaletti. [837] C. R. Chow, C. H. Chu, M. Naraghipour, and M. Hedge. Genetic algorithm approach to fault-tolerant neural networks design. In Proceedings of the World Gongress on Neural Networks – San Diego, volume 3, pages C696–C701, San Diego, CA, 5.-9. June 1994. Lawrence Erlbaum, Hillsdale, NJ. †P63739/95 ga94aCRChow. [838] Hugo de Garis. Growing an artificial brain: The genetic programming of million-neural-net-module artificial brains with trillion cell cellular automata machines. In Sebald and Fogel [1905], page ? †conf.prog ga94adeGaris. [839] Brahma Deo, Amlan Datta, Basant Kukreja, Ravi Rastogi, and Kalyanmoy Deb. Optimization of back propagation algorithm and GAS-assisted ANN models for hot metal desulphurization. Steel Research, 65(12):528–533, December 1994. * EI M082066/95 ga94aDeo. [840] Diane Law and Risto Miikkulainen. Grounding robot control with genetic neural networks. Technical Report AI-94-223, The University of Texas at Austin, Department of Computer Sciences, 1994. * UTCS lop ga94aDianeLaw. [841] G. Di Stefano. New results for neural networks and genetic algorithms in visual field. In ?, editor, Intelligent Engineering Systems Through Artificial Neural Networks, volume 4, pages 599–604, St. Louis, MO, 13.-16. November 1994. ASME, New York. * CCA 67415/96 ga94aDiStephano. [842] Andrej Dobnikar. Genetic synthesis of task-oriented neural networks. 2(4):533–542, 1994. †CCA 12216/95 ga94aDobnikar. Neural Parallel Sci. Comput, [843] Dimitris C. Dracopoulos and Antonia J. Jones. Neuro-genetic adaptive attitude control. Neural Computing & Applications, 2(4):183–204, 1994. ga94aDracopoulos. [844] R. J. Duro, J. Santos, and A. Sarmiento. GENIAL: an evolutionary recurrent neural network designer and trainer. In Proceedings of the 4th International Workshop, pages 295–301, Ontario (Canada), 16.-20. May 1994. Springer-Verlag, Berlin (Germany). †CCA 81499/96 ga94aDuro. [845] David W. White. GANNet: A genetic algorithm for searching topology and weight spaces in neural network design. The first step in finding neural network solution. PhD thesis, University of Maryland College Park, 1994. * DAI Vol. 55 No. 4 ga94aDWWhite. [846] T. M. English. Generalization in populations of recurrent neural networks. In Sebald and Fogel [1905], page ? †conf.prog ga94aEnglish. [847] Pablo A. Estevez and Y. Okabe. Genetic synthesis of piecewise-linear neural networks. In IEEE94/NN [1909], pages –. ga94aEstevez. [848] S. Fujita and H. Nishimura. An evolutionary approach to associative memory in recurrent neural networks. Neural Process., 1(2):9–13, 1994. †CCA 12269/95 ga94aFujita. [849] F. Wong. Genetically optimized neural networks. Report, NIBS Pte Ltd., 1994. †Branke ga94aFWong. Bibliography 107 [850] Geoffrey F. Miller and David T. Cliff. Co-evolution of pursuit and evasion I: Biological and game-theoretic foundations. Report CSRP311, University of Sussex, School of Cognitive and Computing Science, 1994. (ftp://ftp.cogs.susx.ac.uk/pub/reports/csrp/csrp311.ps.Z) ga94aGFMiller. [851] Frédéric C. Gruau. Advances in genetic programming. In Kenneth E. Kinnear, Jr., editor, Advances in Genetic Programming, chapter 24. Genetic micro programming of neural networks, pages 495–518. MIT Press, Cambridge, MA, 1994. †cessu ga94aGruau. [852] Gisbert Schneider and Paul Wrede. Optimizing amino acid sequences by simulated molecular evolution. In Chris Jesshope, Vesselin Jossifov, and Wolfgang Wilhelmi, editors, Proceedings of the Sixth International Workshop on Parallel Processing by Cellular Automata and Arrays (PARCELLA 94), pages 335–246, Potsdam (Germany), 21.-23. September 1994. Akademie Verlag, Berlin. ga94aGSchneider. [853] Kim Kortermand Hansen. Observing, understanding, and controlling the genetic method on a neural network application. Master’s thesis, Aarhus University, Department of Computer Science, 1994. †Aarhus ga94aHansen. [854] Bart L. M. Happel and Jacob M. J. Murre. Design and evolution of modular neural network architectures. Neural Networks, 7(6/7):985–1004, 1994. ga94aHappel. [855] William Eugene Hart. Adaptive global optimization with local search. PhD thesis, University of California, San Diego, 1994. * DAI Vol. 55 No. 7 ga94aHart. [856] Steffen Heine and Ingo Neumann. Optimizing load forecast models using an evolutionary algorithm. In EUFIT’94 [1908], pages 1690–1694. ga94aHeine. [857] J. Heistermann. Different learning algorithms for neural networks - a comperative study. In Davidor et al. [1907], page ? †conf. prog. ga94aHeistermann. [858] Shih-Lin Hung and H. Adeli. A parallel genetic/neural network learning algorithm for MIMD shared memory machines. IEEE Transactions on Neural Networks, 5(6):900–909, November 1994. ga94aHung. [859] R. G. Hutchins. Identifying nonlinear dynamic systems using neural nets and evolutionary programming. In Proceedings of the Twenty-Eighth Asilomar Conference on Signals, Systems, and Computers, volume 2, pages 887–891, Pacific Grove, CA, October 31.- November 2. 1994. IEEE Computer Society Press, Los Alamitos, CA. * CCA 77862/95 ga94aHutchins. [860] Yasumasa Ikuno, Hiroaki Kawabata, Yoshiaki Shirao, Masaya Hirata, Toshikuni Nagahara, and Yashio Inagaki. Application of an improved genetic algorithm to the learning of neural networks. IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences, E77-A(4):731–735, April 1994. ga94aIkuno. [861] Sandeep D. Jain, Pei-Yuan Peng, Anthony Tzes, and Farshad Khorrami. Neural-network designs with genetic learning for control of a single link flexible manipulator. In Proceedings of the 1994 American Control Conference, volume 3, pages 2570–2574, Baltimore, MD, June 29.-July 1. 1994. IEEE, New York. * A95-32052 CCA 14428/95 P62963/95 ga94aJain. [862] J. M. Renders. Algorithmes Génétiques et Réseaux de Neurones. Hermes, Paris (France), 1994. †[1910] ga94aJMRenders. [863] Stefan Jockusch and Helge Ritter. Self-organizing maps: Local competition and evolutionary optimization. Neural Networks, 7(8):1229–1239, 1994. ga94aJockusch. [864] John R. McDonnell and Donald E. Waagen. Evolutionary optimization of cascaded networks. In SuShing Chen, editor, Neural and Stochastic Methods in Image and Signal Processing III, volume SPIE-2304, pages 234–245, ?, June 1994. The International Society for Optical Engineering. * www/SPIE Web ga94aJRMcDonnell. [865] S. Kishi, K. Sugiyama, M. Arafuka, and Y. Hasegawa. Knowledge extraction from neural networks using genetic algorithms. In ?, editor, Proceedings of the International Conference on Neural Networks and Expert Systems in Medicine and Healthcare, pages 53–58, Plymouth (UK), 23.-26. August 1994. University of Plymouth, Plymouth (UK). * CCA 41737/95 ga94aKishi. [866] Hiroaki Kitano. Neurogenetic learning: An integrated method of designing and training neural networks. Physica D, ?(75):225–238, ? 1994. †Branke ga94aKitano. [867] Philipp Koehn. Combining genetic algorithms and neural networks: The encoding problem. Master’s thesis, University of Erlangen and The University of Tennessee, Knoxville, 1994. (ftp://archive.cis. ohio-state.edupub/neuroprose/koehn.encoding.ps.Z) ga94aKoehn. [868] Rajendra Krishnan and Victor B. Ciesielski. 2Delta-Gann: a new approach to training neural networks using genetic algorithms. In Proceedings of the ACNN, pages 194–197, ? 1994. † ga94aKrishnan. 108 Genetic algorithms and neural networks [869] K. K. Kumar and Ellen Smuda. Robust control using ga-optimized neural networks. In Proceedings of the Third IEEE Conference on Control Applications, volume 3, pages 1573–1578, Glasgow (UK), 24.-26. August 1994. IEEE, New York. †CCA 13503/95 ga94aKumar. [870] L. E. Kuo and S. S. Melsheimer. Using genetic algorithms to estimate the optimum width parameter in radial basis function networks. In Proceedings of the 1994 American Control Conference, volume ?, pages 1368–1372, Baltimore, MD, June 29.-July 1. 1994. IEEE, New York. * EI M027497/95 P62963/95 ga94aKuo. [871] İbrahim Kuşçu and Chris Thornton. Design of artificial neural networks using genetic algorithms: Review and prospect. Technical Report Report CSRP319, University of Sussex, School of Cognitive and Computing Science, 1994. (ftp://ftp.cogs.susx.ac.uk/pub/reports/csrp/csrp319.ps.Z) ga94aKuscu. [872] Gideon Langholz, S. A. Barton, and A. B. Markov. Simulated flight control using by bybrid neural network/genetic algorithm architecture. In Proceedings of the Electronic Technology Directions to the Year 2000, pages 150–154, Adelaide (Australia), 23.-25. May 1994. IEEE Computer Society Press, Los Alamitos, CA. †CCA 50997/95 ga94aLangholz. [873] Loi Lei Lai, F. Ndeh-Che, K. H. Chu, P. Rajroop, and X. F. Wang. Design neural networks with genetic algorithms for fault section estimation. In ?, editor, Proceedings of the 29th Universities Power Engineering Conference, volume 2, pages 596–599, Galway (Ireland), 14.-16. September 1994. APC. * EI M040371/95 ga94aLLLai. [874] Timothy T. Maifeld and Gerald B. Sheblé. Short-term load forecasting by a neural network and a refined genetic algorithm. Electric Power Systems Research, 31(3):147–152, December 1994. * EI M077316/94 ga94aMaifeld. [875] Vittorio Maniezzo. Genetic evolution of the topology and weight distribution of neural networks. IEEE Transactions on Neural Networks, 5(1):39–53, January 1994. †Colombetti ga94aManiezzo. [876] John R. McDonnell, W. C. Page, and Don Waagen. Neural network construction using evolutionary programming. In Sebald and Fogel [1905], page ? †conf.prog ga94aMcDonnell. [877] M. McInerney and Atam Dhawan. Training the self-organizing feature map using hybrids of genetic and Kohonen methods. In IEEE94/NN [1909], pages –. ga94aMcInerney. [878] M. I. Dyabin, N. G. Karpinski, A. I. Polovynyuk, V. K. Red’Ko, O. V. Urgant, and V. A. Serechenko. Neurocomputer with binary memory matrix: hardware and application perspectives. In Andrei L. Mikaelian, editor, Optical Memory & Neural Networks ’94, volume SPIE-2430, pages 165–167, ?, December 1994. The International Society for Optical Engineering. * www/SPIE Web ga94aMIDyabin. [879] Orazio Miglino, K. Nafasi, and C. Taylor. Selection for wandering behavior in a small robot. Artificial Life, 2(?):101–116, ? 1994. †[1911] ga94aMiglino. [880] D. Murray. Tuning neural networks with genetic algorithms. AI Expert, 9(6):26–31, June 1994. * CCA 51653/94 ga94aMurray. [881] S. Nara and Wolfgang Banzhaf. Pattern search using genetic algorithms and a neural network model. Complex Systems, 8(4):295–309, August 1994. * EEA 41354/95 CCA 37013/95 ga94aNara. [882] Ari S. Nissinen. Structural optimization of feedforward neural networks using genetic algorithm. Master’s thesis, Tampere University of Technology, Department of Electrical Engineering, Control Engineering Laboratory, 1994. (Report 5; in English) ga94aNissinen. [883] David P. M. Northmore and John G. Elias. Evolving synaptic connections for a silicon neuromorph. In ICEC’94 [1906], pages 753–758. ga94aNorthmore. [884] Zoran Obradović and Rangarajan Srikumar. Evolutionary design of application tailored neural networks. In ICEC’94 [1906], pages 284–289. ga94aObradovic. [885] J. Okamoto, Y. Sugimoto, and S. Hosokawa. A learning method for a feed forward type neural network by GA. Transactions of the Institute of Electronics, Information, and Communication Engineers D-II (Japan), J77D-II(2):461–465, February 1994. (in Japanese) †CCA 41809/94 ga94aOkamoto. [886] Taku Okuno and Yukinori Kakazu. Extraction of embedded hierarchical structure of knowledge from trained boltzmann machine by genetic algorithm. In Proceedings of the Artificial Neural Networks in Engineering Conference, volume 4, pages 327–332, St. Louis, MO, 13.-16. November 1994. ASME, New York. †CCA 61258/96 EI M064502/95 ga94aOkuno. [887] T. Olmez, E. Yazgan, and O. K. Ersoy. Optimised competitive feature vector network. Electronics Letters, 30(24):2052–2053, 24. November 1994. †EI M066343/95 ga94aOlmez. Bibliography 109 [888] David W. Opitz and Jude W. Shavlik. Using genetic search to refine knowledge-based neural networks. In William W. Cohen and Haym Hirsh, editors, Machine Learning, Proceedings of the Eleventh International Conference, pages 208–216, New Brunswick, NJ, 10.-13. July 1994. Morgan Kaufmann, San Mateo, CA. ga94aOpitz. [889] Y. Owechko and S. Shams. Comparison of neural network and genetic algorithms for a resource allocation problem. In IEEE94/NN [1909], pages 4655–4660. ga94aOwechko. [890] Mukesh J. Patel and Vittorio Maniezzo. NN’s and GA’s: evolving co-operative behaviour in adaptive learning agents. In ICEC’94 [1906], pages 290–295. ga94aPatel. [891] Pipatpong Poshyanonda. Genetic neuro-nester. PhD thesis, University of Missouri - Rolla, 1994. * DAI Vol 55 No 10 ga94aPoshyanonda. [892] P. Pratt. Evolving neural networks to control unstable dynamical systems. In Sebald and Fogel [1905], page ? †conf.prog ga94aPratt. [893] Steve G. Romaniuk. Towards minimal network architures with evolutionary growth networks. IEEE94/NN [1909], pages –. ga94aRomaniuk. In [894] S.-S. Han and G. S. May. Modeling the plasma enhanced chemical vapor deposition process using neural networks and genetic algorithms. In Proceedings of the International Conference on Tools with Artificial Intelligence, pages 760–763, New Orlearns, LA, 6.-9.November 1994. IEEE Computer Society Press, Los Alamitos, CA. †EEA 398/95 ga94aS-SHan. [895] Swapan Saha and John P. Christensen. Genetic design of sparse feedforward neural networks. Information Sciences, 79(3-4):191–200, July 1994. ga94aSaha. [896] J. Santos and Richard J. Duro. Evolutionary generation and training of recurrent artificial neural networks. In ICEC’94 [1906], pages 759–763. ga94aSantos. [897] N. Saravanan and David B. Fogel. Evolving neurocontrollers using evolutionary programming. In ICEC’94 [1906], pages 217–222. ga94aSaravanan. [898] Yuji Sato, Shoji Hatano, Hisaaki Hatano, and Tatsumi Furuya. Lookahead planning and co-evolution in recurrent neural networks. In ICEC’94 [1906], pages 764–769. ga94aSato. [899] M. Schoenauer and Edmund Ronald. Genetic Lander: An experiment in accurate neuro-genetic control. In Davidor et al. [1907], pages 452–461. †CCA 46398/95 ga94aSchoenauer. [900] A. Schultz. Data fusion in neural networks via computational evolution. In IEEE94/NN [1909], pages –. ga94aSchultz. [901] Juan Seijas and Jose Sanz-Gonzalez. Evolutive algorithms pioneering neural networks training for artificial vision applications. In IEEE94/NN [1909], pages –. ga94aSeijas. [902] Katsunori Shimohara. Evolutionary systems for brain communications – towards an artificial brain –. In Rodney Brooks and Pattie Maes, editors, Artificial Life IV -Proceedings, pages 3–7, ?, ? 1994. MIT Press. ga94aShimohara. [903] Shu-Chung Leung, Andrew Luk, and Sin-Chun Ng. Fast convergent genetic-type search for multi-layered network. IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences, E77-A(9):1484–1492, September 1994. * EI M057032/95 CCA 507/95 ga94aSHLeung. [904] Sinchai Sittisathanchai. Genetic-neuro scheduler. PhD thesis, University of Missouri - Rolla, 1994. * DAI Vol. 55 No. 2 ga94aSittisathanchai. [905] S. Leung, A. Luk, and S. Ng. A weight evolution algorithm for multi-layered network. In IEEE94/NN [1909], pages –. ga94aSLeung. [906] Robert Smalz and Michael Conrad. Combining evolution with credit apportionment: A new learning algorithm for neural nets. Neural Networks, 7(2):341–351, January 1994. ga94aSmalz. [907] Martha Steenstrup and Gabriele. New results for neural networks and genetic algorithms in visual field diagnosis. In Proceedings of the Artificial Neural Networks in Engineering Conference, pages 599–604, St. Paul, Minnesota, 13.-16. November 1994. ASME, New York. †EI M061935/95 ga94aSteenstrup. [908] Fumiaki Takeda, Saizo Onami, Takashi Kadono, Kengo Terada, and Sigeru Omatu. A paper currency recognition method by a small size neural network with optimized masks by GA. In IEEE94/NN [1909], pages 4243–4246. ga94aTakeda. [909] Lampros Tsinas and Bernd Dachwald. A combined neural and genetic learning algorithm. In ICEC’94 [1906], pages 770–774. ga94aTsinas. 110 Genetic algorithms and neural networks [910] U. Utrecht and K. Trint. Mutation operators for structure evolution of neural networks. In Davidor et al. [1907], pages 492–501. †Branke ga94aUtrecht. [911] E. van Wanrooij. Evolving sequential neural networks for time series forecasting. Master’s thesis, University of Utrecht, Department of Computer Science, 1994. †Branke ga94aWanrooij. [912] Gerhard Weiß. Neural networks and evolutionary computation. part I: Hybrid approaches in artificial intelligence. In ICEC’94 [1906], pages 268–272. ga94aWeiss. [913] William J. Wolfe. Hybrid Hopfield networks. In David P. Casasent, editor, Intelligent Robots and Computer Vision XIII: Algorithms and Computer Vision, volume SPIE-2353, pages 364–374, ?, October 1994. The International Society for Optical Engineering. * www/SPIE Web ga94aWJWolfe. [914] K. Worden, G. R. Tomilinson, and A. P. Burrows. Fault detection employing transducer optimization procedures. In ?, editor, European Conference on Smart Structures and Materials, volume SPIE-2361, pages 36–46, Manchester (UK), 12. -14. October 1994. The International Society for Optical Engineering. * A95-15705 ga94aWorden. [915] Wen Wu and Richard J. Mammone. Relabeling exchange method REM for learning in neural networks. In James L. Flanagan, Richard J. Mammone, Albert E. Brandenstein, Edward R. Pike, Stelios C. Thomopoulos, Marie-Paule Boyer, H. K. Huang, and Osman M. Ratib, editors, Substance Identification Analytics, volume SPIE-2093, pages 254–263, ?, February 1994. The International Society for Optical Engineering. * www/SPIE Web ga94aWWu. [916] Yuichi Ishizuka. Neuro computer, 1994. (JP patent no. 6187473. Issued July 8 1994) * fi.espacenet.com ga94aYIshizuka. [917] Byungjoo Yoon, Dawn J. Holmes, Gideon Langholz, and Abraham Kandel. Efficient genetic algorithms for training layered feedforward neural networks. Information Sciences, 76(1-2):67–85, 1994. * ga94aYoon. [918] J. Arabas. A genetic approach to the Hopfield neural-network in the optimization problems. Bulletin of the Polish Academy of Sciences - Chemistry, 42(1):59–66, ? 1994. (Proceedings of the XVI National Conference on Circuit Theory and Electronic Circuits, Kolobrzeg (Poland), Oct. 26.-28., 1993) †P62802/94 ga94bArabas. [919] Joachim Born and Ivan Santibáñez-Koref. Evolutionary structuring of neural networks by solving a binary problem. In U. Derings, A. Bachem, and A. Drexl, editors, Operations Research Proceedings, pages 394–399. Springer-Verlag, Berlin, 1994. †Born ga94bBorn. [920] Heinrich Braun and Peter Zagorski. ENZO-II – a powerful design tool to evolve multilayer feed forward networks. In ICEC’94 [1906], pages 278–283. ga94bBraun. [921] Byoung-Tak Zhang and Heinz Mühlenbein. Synthesis of sigma-pi neural networks by the breeder genetic programming. In ICEC’94 [1906], pages 318–323. ga94bBTZhang. [922] E. V. Budilova, A. T. Terekhin, and S. A. Chepurnov. A genetic algorithm for optimization of neural networks capable of learning to search for food in a maze. Radiophys. Quantum Electron. (USA), 37(9):749– 755, 1994. Translation of: Izv. Vyssh. Uchebn. Zaved. Radiofiz. (Russia) p. 1162-1172 †CCA26623/96 ga94bBudilova. [923] C. R. Chow, C. H. Chu, M. Naraghi-Pour, and M. Hegde. Genetic algorithm approach to fault-tolerant neural networks design. In ?, editor, Proceedings of the 1994 International Neural Networks Society Annual Meeting, volume 3, pages 696–701, San Diego, CA (USA), 5.-9. June 1994. Lawrence Erlbaum Associates, Hillsdale, NJ (USA). * CCA51966/94 ga94bChow. [924] Ching Zhang and Fangju Wang. Genetic algorithm for molecular sequence comparison. In Proceedings of the 1994 IEEE International Conference on Systems, Man, and Cybernetics, volume 3, pages 2242–2247, San Antonio, TX, 2.-5. October 1994. IEEE, New York. * EI M096133/95 ga94bCZhang. [925] David E. Moriarty and Risto Miikkulainen. Evolving neural networks to focus mini-max search. In ?, editor, Proceedings of the Tweftth National Conference on Artificial Intelligence, volume 2, pages 1371–1377, Seattle, WA, 31. July-4. August 1994. AAAI Press / The MIT Press. * EI M027527/95 ga94bDEMoriarty. [926] Dimitris C. Dracopoulos and Antonia J. Jones. An adaptive neurocontrol design applied to the attitude control problem. In ?, editor, Applications of artificial neural networks V, volume SPIE-2243, pages 380– 391, Orlando, FL, 5. -8. April 1994. The International Society for Optical Engineering. * A95-12855 ga94bDracopoulos. [927] D. T. Pham and D. Karaboga. Design of an adaptive fuzzy logic controller. In Proceedings of the 1994 IEEE International Conference on Systems, Man, and Cybernetics, volume 1, pages 437–442, San Antonio, TX, 2.-5. October 1994. IEEE, New York. * EI M095962/95 ga94bDTPham. Bibliography 111 [928] Pablo A. Estevez and Y. Okabe. Evolutionary structuring of max-min propagation nets. In ?, editor, Proceedings of the 1994 International Neural Network Society Annual Meeting, volume 4, pages 465–469, San Diego, CA, USA, 5.-9. June 1994. Lawrence Erlbaum Associates, Hillsdale, NJ, USA. * CCA58245/95 ga94bEstevez. [929] Suju M. George, Kirti Singh, Ashutosh Saxena, and P. RamBabu. Use of recurrent networks and genetic algorithms for solving standard cell placement problem. In EUFIT’94 [1908], pages 1242–1246. ga94bGeorge. [930] Frédéric C. Gruau. Neural network synthesis using cellular encoding and the genetic algorithm. PhD thesis, Ecole Normale Superieure de Lyon, Laboratoire de l’Informatique du Parallilisme, 1994. ga94bGruau. [931] Gisbert Schneider, Johannes Schuchhardt, and Paul Wrede. Artificial neural networks and simulated molecular evolution are potential tools for sequence-oriented protein design. Computer Applications in the Biosciences (CABIOS), 10(6):635–645, 1994. †[1592] ga94bGSchneider. [932] Philip Husbands, Inman Harvey, Dave Cliff, and G. Miller. The use of genetic algorithms for the development of sensorimotor control systems. In Proceedings of the from Perception to Action Conference, pages 110–121, Lausanne (Switzerland), 7.-9. September 1994. IEEE Computer Society Press, Los Alamitos, CA. †CCA 46523/95 ga94bHusbands. [933] C. Jacob. Typed expressions evolution of artificial nervous systems. In ICEC’94 [1906], pages 502–507. ga94bJacob. [934] Kim Jongwan, Ahn Jesung, Kim Chong Sang, Cho Seongwon, and Hwang Heeyeung. Pattern recognition using competitive learning neural network with the reduced input dimension. J. Korea Inf. Sci. Soc. (South Korea), 21(10):1919–1926, 1994. †CCA730/95 ga94bJongwan. [935] Werner Kinnebrock. Accelerating the standard backpropagation method using a genetic approach. ?, ?(?):583–588, 1994. †EI M048058/95 ga94bKinnebrock. [936] John R. McDonnell and Don E. Waagen. Evolving recurrent perceptrons for time-series modeling. IEEE Transactions on Neural Networks, 5(1):24–38, January 1994. ga94bMcDonnell. [937] Masahiro Tanaka, Hisashi Koga, and Tetsuzo Tanino. An application of the genetic algorithm to the structure determination of a neural network. Transactions of the Institute of Systems, Control and Information Sciences, 7(12):528–530, ? 1994. (in Japanese) ga94bMTanaka. [938] Steve G. Romaniuk. Applying crossover operators to automatic neural network construction. In ICEC’94 [1906], pages 750–752a. ga94bRomaniuk. [939] Tom Routen. Genetic algorithm and neural network approaches to local access network design. In Vijay Madisetti, Erol Gelenbe, and Jean Walrand, editors, Proceedings of the 2nd IEEE International Workshop on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems, pages 239–243, Durham, NC, 31. January-2. February 1994. IEEE, New York. * EI M125159/95 ga94bRouten. [940] Fumiaki Takeda, Sigeru Omatu, Saizo Onami, Takashi Kadono, and Kengo Terada. A paper currency recognition method by a neural network using masks and mask optimization by GA. In Proceedings of the Advances in Fuzzy Logic, Neural Networks and Genetic Algorithms, pages 125–129, Nagoya (Japan), 9.-10. August 1994 1994. Springer-Verlag, Berlin (Germany). ga94bTakeda ⇒ ga94WWW. [941] L. Vermeersch, F. Dumortier, and G. Vansteenkiste. Genetic algorithms as optimisers for feedforward neural networks. In ?, editor, Proceedings of the International Conference on Artificial Neural Networks, volume 1, pages 509–516, Sorrento, Italy, 26.-29. May 1994. Springer-Verlag, Berlin (Germany). †CCA87415/95 ga94bVermeers. [942] Gerhard Weiß. Neural networks and evolutionary computation. part II: Hybrid approaches in the neurosciences. In ICEC’94 [1906], pages 273–277. ga94bWeiss. [943] B.-T. Zhang. Effects of Occam’s razor in evolving sigma-pi neural networks. In Davidor et al. [1907], pages 462–471. †Branke ga94cBTZhang. [944] David E. Moriarty and Risto Miikkulainen. Evolutionary neural networks for value ordering in constraint satisfaction problems. Technical Report AI-94-218, The University of Texas at Austin, Department of Computer Sciences, 1994. * UTCS lop ga94cDEMoriarty. [945] Frédéric C. Gruau. Automatic definition of modular neural networks. Adaptive Behavior, 3(2):151–183, Fall 1994. * A95-33447 ga94cGruau. [946] Gisbert Schneider and Paul Wrede. The rational design of amino acid sequences by artificial neural networks and simulated molecular evolution: De novo design of an idealised leader peptidase cleavage-site. Biophysical Journal, 66(?):335–344, 1994. †David E. Clark/bib ga94cGSchneider. 112 Genetic algorithms and neural networks [947] C. Jacob. Evolution of typed expressions describing artificial nervous systems. In Proceedings of the International Conference on Artificial Neural Networks, volume 1, pages 258–262, Sorrento, Italy, 26.29. May 1994. Springer-Verlag, Berlin (Germany). †CCA87377/95 ga94cJacob. [948] Chris Nikolopoulos. Using classifier systems to design neural nets. In Proceedings of the International Conference on Tools with Artificial Intelligence, pages 812–815, New Orlearns, LA, 6.-9.November 1994. IEEE Computer Society Press, Los Alamitos, CA. †CCA 2744/95 ga94cNikolopoulos. [949] Marc Schoenauer and Edmund Ronald. Neuro-genetic truck backer-upper controller. In ICEC’94 [1906], pages 720–723. ga94cSchoenauer. [950] Sankar K. Pal and Dinabandhu Bhandari. Genetic algorithms with fuzzy fitness function for object extraction using cellular networks. Fuzzy Sets and Systems, 65(2-3):129–139, 10. August 1994. * EI M027479/95 CCA 76179/94 ga94cSKPal. [951] Darrell Whitley, Stephen Dominic, Rajarshi Das, and Charles W. Anderson. chapter Genetic reinforcement learning for neurocontrol problems, page ? 1994. †www.amazon.com ga94cWhitley. [952] P. P. C. Yip and Y.-H. Pao. Growing universal neural networks using GESA. In Sebald and Fogel [1905], page ? †conf.prog ga94cYip. [953] D. Zhang and M.I. Elmasry. Evolutionary computation for neural networks. In IEEE94/NN [1909], pages –. ga94cZhang. [954] Peter J. Angeline, Gregory M. Saunders, and Jordan B. Pollack. An evolutionary algorithm that constructs recurrent neural networks. IEEE Transactions on Neural Networks, 5(1):54–65, January 1994. †toc ga94dAngeline. [955] Sankar K. Pal and Dinabandhu Bhandari. Selection of optimal set of weights in a layered network using genetic algorithm. Information Sciences, 80(3-4):213–234, September 1994. ga94dSKPal. [956] M. A. El-Sharkawi and S. J. Huang. Application of genetic-based neural networks to power system static security assessment. In ?, editor, Proceedings of the International Conference on Intelligent System Application to Power Systems, page ?, Montpellier (France), 5.-9. September 1994. ? †prog. ga94ElSharkawi. [957] Charles L. Karr. Deducing process information with neural networks and genetic algorithm. Fluid / Particle Separation Journal, 7(4):155–159, December 1994. ga94gKarr. [958] Hugo de Garis. An artificial brain: ATR’s CAM-brain project aims to build/evolve an artificial brain with a million neural net modules inside a trillion cell cellular automata machine. New Generation Computing Journal, 12(2):?, ? 1994. †[1912] De Garis ga94hdeGaris. [959] Hugo de Garis. CAM-BRAIN: Growing an artificial brain with a million neural net modules inside a trillion cell cellular automata machine. Journal of the Society of Instrument and Control Engineers, 33(2):?, ? 1994. †De Garis ga94ideGaris. [960] Charles L. Karr and P. A. Vann. Inferring difficult to measure parameters using neural networks and genetic algorithms. In Artificial Neural Networks in Engineering (ANNIE’94), volume 4, pages 313–319, St. Louis, MO, 13.-16. November 1994. ASME, New York. * ga94iKarr. [961] Ricardo Skaf Abdala and Weber Martins. Sistema genetico hierarquico para escolha topolsgica de redes neurais booleanas [A hierarchical genetic system for selecting topology of boolean neural networks]. In ?, editor, Proceedings of the Second Brazilian Symposium on Neural Networks, page ?, Sao Carlos, SP - Brazil, 18.-20. October 1995. The Brazilian Computer Science Society. (in Portuguese) †conf. prog. ga95aAbdala. [962] M. I. A. Abdalla. Genetic algorithm for learning neural networks. Egypt. Comput. J. (Egypt), 23(2):132– 148, 1995. †CCA 626/97 ga95aAbdalla. [963] A. H. Abu-Alola and N. E. Gough. Identification and adaptive control of nonlinear processes using combined neural networks and genetic algorithms. In Pearson et al. [1913], pages 396–399. ga95aAbu-Alola. [964] Andreas Draeger, Sebastian Engell, and Horst Ranke. Model predictive control using neural networks. IEEE Control Systems Magazine, 15(5):61–66, October 1995. ga95aADraeger. [965] A. H. Jones. Genetic tuning of neural non-linear PID controllers. In Pearson et al. [1913], pages 412–415. ga95aAHJones. [966] Antonia J. Jones. Neural networks and genetic algorithms for prediction and control of dynamic systems. In ?, editor, Proceedings of the Second Brazilian Symposium on Neural Networks, page ?, Sao Carlos, SP Brazil, 18.-20. October 1995. The Brazilian Computer Science Society. †conf. prog. ga95aAJJones. Bibliography 113 [967] Masaki Arao, Yasuhiro Tsutsumi, Toshio Fukuda, and Koji Shimojima. Flexible intelligent system based on fuzzy, neural networks and reinforcement learning. In Proceedings of the 1995 IEEE International Conference on Fuzzy Systems, volume 5, pages 69–70, Yokohama (Japan), 20.-24. March 1995. IEEE, Piscataway, NJ. * EI M163909/95 ga95aArao. [968] Armin Schneider. Adaptive system for generating neural networks using genetic algorithms. In Steven K. Rogers and Dennis W. Ruck, editors, Applications and Science of Artificial Neural Networks, volume SPIE2492, pages 284–292, ?, April 1995. The International Society for Optical Engineering. * www/SPIE Web ga95aASchneider. [969] A. Ugur and Michael Conrad. Multiple level evolutionary learning in neuronal pattern recognition. In ?, editor, Proceedings of the Fourth Annual Conference on Evolutionary Programming, pages 271–288, San Diego, CA, 1.-3. March 1995. MIT Press, Cambridge, MA. †CCA34467/97 ga95aAUgur. [970] Karthik Balakrishnan and Vasant Honavar. Evolutionary design of neural architectures – preliminary taxonomy and guide to literature. Technical Report CS TR #95-01, Iowa State University, Artificial Intelligence Group, 1995. †[1316] Branke ga95aBalakrishnan. [971] Shumeet Baluja. Practical handbook of genetic algorithms. In Chambers [1914], chapter 1. Artificial neural network evolution: Learning to steer a land vehicle, pages 31–51. ga95aBaluja. [972] Barbro Back, Kaisa Sere, and Michiel C. van Wezel. Choosing the best set of bankruptcy predictors. In Alander [1915], pages 285–301. (ftp://ftp.uwasa.fics/1NWGA/Back.ps.Z) ga95aBBack. [973] George Bebis and Michael Georgiopoulos. Improving generalization by using genetic algorithms to determine the neural network size. In Proceedings of the Southcon /95, pages 392–397, Ft. Lauderdale, FL, ? 1995. IEEE, New York. ga95aBebis. [974] J. L. Bernier, J. J. Merelo, J. Ortega, and A. Prieto. Test pattern generation for analog circuits using neural networks and evolutive algorithms. In ?, editor, From Natural to Artificial Neural Computation, pages 838–844, Malaga-Torremolinos (Spain), 7.-9. June 1995. Springer-Verlag, Berlin. * EEA 38338/96 ga95aBernier. [975] Steve A. Billings and Guang L. Zheng. Radial basis function network configuration using genetic algorithm. Neural Networks, 8(6):877–890, ? 1995. ga95aBillings. [976] B. M. Wise, B. R. Holt, N. B. Gallagher, and S. Lee. A comparison of neural networks, non-linear biased regression and a genetic algorithm for dynamic model identification. Chemometrics and Intelligent Laboratory Systems, 30(?):81–89, ? 1995. †David E. Clark/bib ga95aBMWise. [977] Egbert J. W. Boers, Marko V. Borst, and Ida G. Sprinkhuizen-Kuyper. Evolving neural networks using the “Baldwin effect”. In Pearson et al. [1913], pages 333–336. ga95aBoers. [978] Newton Chaves Kras Borges, Paulo M. Engel, and Claudio Fernando R. Geyer. Um estudo de paralelismo em redes backpropagation. In ?, editor, Proceedings of the Second Brazilian Symposium on Neural Networks, page ?, Sao Carlos, SP - Brazil, 18.-20. October 1995. The Brazilian Computer Science Society. (in Portuguese) †conf. prog. ga95aBorges. [979] Jürgen Branke, Udo Kohlmorgen, and Hartmut Schmeck. A distributed genetic algorithm improving the generalization behaviour of neural networks. In Nada Lavraç and Stefan Wrobel, editors, Proceedings of the 8th European Conference on Machine Learning (ECML-95), volume 914 of Lecture Notes in Artificial Intelligence, pages 107–121, Heraclion (Greece), 25.-27. April 1995. Springer-Verlag, Berlin. ga95aBranke. [980] T. W. Brotherton and P. K. Simpson. Dynamic feature set training of neural nets for classification. In McDonnell et al. [1916], page ? †conf.prog ga95aBrotherton. [981] Byoung-Tak Zhang, P. Ohm, and Heinz Mühlenbein. Learning to predict by evolutionary neural trees. In ?, editor, Proceedings of the 1995 International Neural Network Society Annual Meeting, volume 1, pages 823–826, Washington, DC (USA), 17.-21. July 1995. Lawrence Erlbaum Associates, Mahwah, NJ (USA). †CCA49060/97 ga95aByoZhang. [982] C. E. Floyd and G. D. Tourassi. Computer aided diagnosis using genetic algorithms and neural networks. In ?, editor, Proceedings of the 1995 International Neural Network Society Annual Meeting, volume 2, pages 863–866, Washington, DC (USA), 17.-21. July 1995. Lawrence Erlbaum Associates, Mahwah, NJ (USA). †EEA57538/97 ga95aCEFloyd. [983] David T. Cliff. Neuroethology, computational. In M. A. Arbib, editor, Handbook of Brain Theory and Neural Networks. MIT Press, 1995. (to appear; also as [834]; ftp://ftp.cogs.susx.ac.uk/pub/reports/ csrp/csrp338ps.Z) ga95aCliff. 114 Genetic algorithms and neural networks [984] D. W. Coir and A. E. Smith. Using a neural network as a function evaluator during GA search for reliability optimization. In Proceedings of the Artificial Neural Networks in Engineering (ANNIE’95), volume 5, pages 369–374, St. Louis, MO, 12.-15. November 1995. ASME Press, New York, NY. †EEA10364/97 ga95aCoir. [985] Hugo de Garis. CAM-BRAIN the evolutionary engineering of a billion neuron artificial brain by 2001 which grows/evolves at electronic speeds inside a cellular automata machine (CAM). In Pearson et al. [1913], pages 84–87. ga95adeGaris. [986] Berna Dengiz, Fulya Altiparmak, and Alice E. Smith. A genetic algorithm approach to optimal topological design of all terminal networks. In Proceedings of the Artificial Neural Networks in Engineering (ANNIE’95), volume 5, pages 405–410, St. Louis, MO, 12.-15. November 1995. ASME Press, New York, NY. †CCA17185/97 ga95aDengiz. [987] Andrej Dobnikar. Genetic synthesis of task oriented neural networks. In Pearson et al. [1913], pages 329–332. ga95aDobnikar. [988] Stephan Dreiseitl and Witold Jacak. Genetic algorithm based neural networks for dynamical system modeling. In ICEC’95 [1917], pages 602–607. †prog. ga95aDreiseitl. [989] D. T. Pham and S. Sagiroglu. Three methods of training multi-layer perceptrons to model a robot sensor. Robotica, 13(5):531–538, September-October 1995. ga95aDTPham. [990] Ian R. East and Jon Rowe. The evolution of morphology using Kauffman nets. In IEE/IEEE Sheffield ’95 [1918], pages 259–264. †conf.prog ga95aEast. [991] Pablo A. Estevez. Designing max-min propagation neural networks by hyperplane switching. In ICEC’95 [1917], pages 596–601. †prog. ga95aEstevez. [992] A. Fadda and M. Schoenaur. Evolutionary chromatographic law identification by recurrent neural nets. In McDonnell et al. [1916], page ? †conf.prog ga95aFadda. [993] Shou King Foo, P. Saratchandran, and N. Sundararajan. Genetic algorithms based pattern allocation schemes for training set parallelism in backpropagation neural networks. In ICEC’95 [1917], pages 545– 550. †prog. ga95aFoo. [994] I. G. French, S. Ho, and A. Adgar. Comparison of identification techniques for nonlinear systems. In Pearson et al. [1913], pages 519–522. ga95aFrench. [995] E. S. Gelsema. Abductive reasoning in Bayesian belief networks using a genetic algorithm. Pattern Recognition Letters, 16(?):865–871, August 1995. ga95aGelsema. [996] G. Liu and V. Kadirkamanathan. Multiobjective criteria for neural network structure selection and identification using genetic algorithms. In McDonnell et al. [1916], page ? †conf.prog ga95aGLiu. [997] J. B. Golden. Evolutionary optimization of a neural network-based signal processor for photometric data from an automated DNA sequencer. In McDonnell et al. [1916], page ? †conf.prog ga95aGolden. [998] Garrison W. Greenwood. Applications of evolutionary strategies in training partially recurrent neural networks. In Ošmera [1919], pages 53–58. ga95aGreenwood. [999] Gisbert Schneider, Johannes Schuchhardt, and Paul Wrede. Peptide design in machina: Development of artificial mitochondrial protein precursor cleavage sites by simulated molecular evolution. Biophysical Journal, 68(?):434–447, 1995. †David E. Clark/bib ga95aGSchneider. [1000] Ari Hämäläinen. Using genetic algorithm in self-organizing map design. In Pearson et al. [1913], pages 364–367. ga95aHamalainen. [1001] A. Häßler, Y. Li, D. J. Murray-Smith, and K. C. Sharman. Neurocontrollers designed by a genetic algorithm. In IEE/IEEE Sheffield ’95 [1918], pages 536–542. †conf.prog ga95aHaussler. [1002] Reinhold Huber, Helmut A. Mayer, and Roland Schwaiger. netGen – A parallel system generating problemadapted topologies of artificial neural networks by means of genetic algorithms. In ?, editor, Beiträge zum 7. Fachgruppentreffen Maschinelles Lernen der GI-Fachgruppe 1.1.3. Forschungsbericht Nr. 580, pages 91–98, Dortmund (Germany), August 1995. ? †[?] ga95aHuber. [1003] Philip Husbands, Inman Harvey, and David T. Cliff. Circle in the round: State space attractors for evolved sighted robots. Robotics and Autonomous Systems, 15(1-2):83–106, July 1995. ga95aHusbands. [1004] H. Yamamoto. Recognition system of hand-written figures by using neural networks and genetic algorithm. In ?, editor, Proceedings of the Computer Applications in Production and Engineering, volume ?, pages 642–649, Beijing (China), May 1995. Chapman & Hall, London, UK. †CCA22082/97 ga95aHYamamoto. [1005] L. C. Jain. Hybrid connectionist systems in research and teaching. IEEE Aerospace and Electronic Systems Magazine, 10(3):14–18, March 1995. ga95aJain. Bibliography 115 [1006] J. A. Shine. A genetic algorithm approach for configuring backpropagation architectures for imagery classification. In ?, editor, Proceedings of the International Neural Network Society Annual Meeting, volume 1, pages 783–786, Washington, DC, 17.-21. July 1995. Lawrence Erlbaum Associates, Mahwah, NJ (USA). †EEA57429/97 ga95aJAShine. [1007] Jason James and Cihan H. Dagli. Use of genetic algorithms for encoding efficient neural network architectures: neurocomputer implementation. In Steven K. Rogers and Dennis W. Ruck, editors, Applications and Science of Artificial Neural Networks, volume SPIE-2492, pages 323–330, ?, April 1995. The International Society for Optical Engineering. * www/SPIE Web ga95aJasonJames. [1008] Il-Kwon Jeong, Changkyu Choi, Jin-Ho Shin, and Ju-Jang Lee. A modified genetic algorithm for neurocontrollers. In ICEC’95 [1917], pages 306–311. †prog. ga95aJeong. [1009] Jong-Hwan Kim, Hyun Myung, and Jeong-Yul Jeon. Hybrid evolutionary programming with fast convergence for constrained optimization problems. In Korea-Australia EC’95 [1920], pages 246–257. ga95aJHKim. [1010] Jinwoo Kim, Yoonkeon Moon, and Bernard P. Zeigler. Designing fuzzy net controllers using genetic algorithms. IEEE Control Systems, 15(3):66–72, June 1995. ga95aJKim. [1011] Jason Kingdon and Laura Dekker. The shape of space. In IEE/IEEE Sheffield ’95 [1918], pages 543–548. †conf.prog ga95aKingdon. [1012] Uwe Kohlmorgen, H. Bruce Penfold, and Hartmut Schmeck. Deriving fault tolerant application-specific neural nets using a massively parallel genetic algorithm. In Alander [1915], pages 123–134. (ftp://ftp. uwasa.fics/1NWGA/Kohlmorgen1.ps.Z) ga95aKohlmorgen. [1013] Ernst M. Kussul and Tatyana N. Baidyk. Genetic algorithm for neurocomputer image recognition. In Pearson et al. [1913], pages 120–123. ga95aKussul. [1014] K. Worden, A. P. Burrows, and G. R. Tomlinson. A combined neural and genetic approach to sensor placement. In ?, editor, Proceedings of the 13th International Modal Analysis Conference, volume 2, pages 1727–1736, Nashville, TN, 13.-16. February 1995. Society for Experimental Mechanics, Inc., Bethel, CT. * A95-25126 ga95aKWorden. [1015] Anna Loskiewicz-Buczak and Robert E. Uhrig. Information fusion by fuzzy set operation and genetic algorithms. Simulation, 65(1):51–66, July 1995. ga95aLoskiewicz-Buczak. [1016] S. M. Lucas. The open ended evolution of neural networks. In IEE/IEEE Sheffield ’95 [1918], pages 388–393. †conf.prog ga95aLucas. [1017] A. M. C. Machado and M. F. M. Campos. Training neural networks with influence diagrams. In Xin Yao, editor, Progress in Evolutionary Computation. Proceedings of the AI’93 and AI’94 Workshops on Evolutionary Computation, volume 956 of Lecture Notes in Artificial Intelligence, pages 245–256, Melbourne and Armidale (Australia), 16. November 1993 and 21.-22. November 1994 1995. Springer Verlag, Berlin. †Yao /conf. prog. ga95aMachado. [1018] Rustom Mamlook and Wiley E. Thompson. Multiple-class identification algorithm using genetic neural networks. In Proceedings of the International Conference on Electronics, Circuits and Systems, pages 399–404, Amman, Jordan, 17.-21. December 1995. Higher Council for Sci. & Technol., Amman, Jordan. †EEA117862/96 ga95aMamlook. [1019] Martin Mandischer. Evolving recurrent neural networks with non-binary encoding. In ICEC’95 [1917], pages 584–589. †prog. ga95aMandischer. [1020] Mitchell A. Potter and Kenneth A. De Jong. Evolving neural networks with collaborative species. In ?, editor, Proceedings of the Twenty-Seventh Annual Summer Computer Simulation Conference, volume ?, pages 340–345, Ottawa, Ont., Canada, 24.-26. July 1995. Society for Computer Simulation, San Diego, CA. †CCA43297/97 ga95aMAPotter. [1021] J. J. Merelo and A. Prieto. G-LVQ, a combination of genetic algorithms and LVQ. In Pearson et al. [1913], pages 92–95. ga95aMerelo. [1022] Mohamad H. Hassoun. Fundamentals of Artificial Neural Networks. MIT Press, Cambridge, MA, 1995. ga95aMHHassoun ⇒ http://neuron.eng.wayne.edu/. [1023] Olivier Michel and Joëlle Biondi. From the chromosome to the neural network. In Pearson et al. [1913], pages 80–83. ga95aMichel. [1024] Mary Lou Padgett, Eleanor M. Josephson, C. R. White, and Don W. Duffield. Clustering, simulation, and neural networks in real-world applications. In Steven K. Rogers and Dennis W. Ruck, editors, Applications and Science of Artificial Neural Networks, volume SPIE-2492, pages 562–572, ?, April 1995. The International Society for Optical Engineering. * www/SPIE Web ga95aMLPadgett. 116 Genetic algorithms and neural networks [1025] Mark Watson. C++ Power Paradigms. McGraw-Hill, Inc., New York, 1995. †Mallat ga95aMWatson. [1026] Roman Neruda. Functional equivalence and genetic learning of RBF networks. In Pearson et al. [1913], pages 53–56. ga95aNeruda. [1027] Nigel Snoad and Terry Bossomaier. MONSTER - the ghost in the connection machine: modularity of neural systems in theoretical evolutionary research. In Proceedings of the ACM/IEEE Supercomputing Conference, volume 1, pages 578–601, San Diego, CA (USA), 3.-8. December 1995. IEEE, Los Alamitos, CA. †EI M086526/97 ga95aNigSnoad. [1028] Omar Syed. Applying genetic algorithms to recurrent neural networks for learning network parameters and architecture. Master’s thesis, Case Western Reserve University, Department of Electrical Engineering, 1995. ga95aOmarSyed. [1029] Tomasz Ostrowski. Computing with genetic algorithms in the context of adaptive neural filtering. Pattern Recognition Letters, 16(2):125–132, February 1995. ga95aOstrowski. [1030] Z. R. Petrovic, S. L. Ivanovic, and Z. A. Spasic. Integration of neural networks and genetic algorithms: an example of machine noise diagnosis. In Proceedings of the First World Congress on Intelligent Manufacturing Processes and Systems, volume 2, pages 962–971, San Juan, Puerto Rico, 13.-17. February 1995. Univ. Puerto Rico, San Juan, Puerto Rico. †CCA33245/97 ga95aPetrovic. [1031] Patrick M. Wong, Tamás D. Gedeon, and Ian J. Taggart. An improved technique in porosity prediction: a neural network approach. IEEE Transactions on Geoscience and Remote Sensing, 33(4):971–980, July 1995. ga95aPMWong. [1032] John R. Podlena and Tim Hendtlass. Evolving complex neural networks that age. In ICEC’95 [1917], pages 590–595. †prog. ga95aPodlena. [1033] Luis Rabelo, Albert Jones, and Yuehwern Yih. Practical handbook of genetic algorithms. In Chambers [1914], chapter 9. A hybrid approach using neural networks, simulation, genetic algorithms, and machine learning for real-time sequencing and scheduling problems, pages 197–220. ga95aRabelo. [1034] Rustom Mamlook and Wiley E. Thompson. Multiple-class identification algorithm using genetic neural networks. In Ivan Kadar and Vibeke Libby, editors, Signal Processing, Sensor Fusion, and Target Recognition IV, volume SPIE-2484, pages 681–688, ?, July 1995. The International Society for Optical Engineering. * www/SPIE Web ga95aRMamlook. [1035] Stephen G. Roberts and Mike Turega. Evolving neural network structures: An evaluation of encoding techniques. In Pearson et al. [1913], pages 96–99. ga95aRoberts. [1036] Steve G. Romaniuk. Evolutionary grown semi-weighted neural networks. In Eshelman [1921], page ? †prog ga95aRomaniuk. [1037] Philip B. James-Roxby. A neural network implementation for an electronic nose. In Pearson et al. [1913], pages 424–427. ga95aRoxby. [1038] Shyh-Jier Huang and Ching-Lien Huang. Genetic-based multi-layered perceptrons for Taiwan Power system short term load forecasting. In Proceedings of the Artificial Neural Networks in Engineering (ANNIE’95), volume 5, pages 785–790, St. Louis, MO, 12.-15. November 1995. ASME Press, New York, NY. †CCA16780/97 ga95aS-JHuang. [1039] Rameri Salama and Philip Hingston. Evolving neural network controllers. In ICEC’95 [1917], pages 579–583. †prog. ga95aSalama. [1040] Y. Sato and T. Ochiai. 2-D genetic algorithms for determining neural network structure and weights. In McDonnell et al. [1916], page ? †conf.prog ga95aSato. [1041] J. Schäfer and H. Braun. Optimizing classifiers for handwritten digits by genetic algorithms. In Pearson et al. [1913], pages 10–13. ga95aSchafer. [1042] S. Chen, Y. Wu, and K. Alkadhimi. A two-layer learning method for radial basis function networks using combined genetic and regularised OLS algorithms. In IEE/IEEE Sheffield ’95 [1918], pages 245–249. †conf.prog ga95aSChen. [1043] Susmita De, Ashish Ghosh, and Sankar K. Pal. An application of genetic algorithms to evolve Hopfield type optimum network architectures for object extraction. In ICEC’95 [1917], pages 504–508. †prog. ga95aSDe. [1044] Seok-Hee Lee and Hyuek-Jae Lee. New NHN(neural network with hybrid neurons) model based on evolutionary programming. In Korea-Australia EC’95 [1920], page 17. ga95aSHLee. Bibliography 117 [1045] Shigeru Kashiwagi. Learning system of recurrent neural network of coupling type, 1995. (JP patent no. 7044512. Issued February 14 1995) * fi.espacenet.com ga95aSKashiwagi. [1046] Martin Šojdr. Minimizing the redundancy in layered neural networks using evolutionary approach. In Ošmera [1919], pages 155–158. ga95aSojdr. [1047] T. R. Stratton. Genetically connected artificial neural networks. In Proceedings of the 1995 International Neural Network Society Annual Meeting, volume 3, pages 219–222, Washington D.C. (USA), 17.-21. July 1995. Lawrence Erlbaum Associates, Mahwah, NJ (USA). †CCA46054/97 ga95aStratton. [1048] K. S. Tang, C. Y. Chan, K. F. Man, and S. Kwong. Genetic structure for NN topology and weights optimization. In IEE/IEEE Sheffield ’95 [1918], pages 250–255. †conf.prog ga95aTang. [1049] Takeshi Aoki, A. Ishiguro, Tatsuya Suzuki, and Shigeru Okuma. Realization of 2 DOF control system using multilayered neural networks. Nippon Kikai Gakkai Ronbunshu C Hen, 61(588):3289–3294, 1995. * EI M199232/95 ga95aTAoki. [1050] Tammy Manneer and Ajit Narayanan. Quantum-inspired neural networks. Technical Report R329, University of Exeter, Department of Computer Science, 1995. ga95aTMenneer. [1051] Tom Williams. Fuzzy, neural and genetic methods train to overcome complexity. Computer Design, 34(5):59–76, May 1995. ga95aTWilliams. [1052] R. M. Vahidov, M. A. Vahidov, and Z. E. Eyvazova. Use of genetic and neural technologies in oil equipment computer-aided design. In Pearson et al. [1913], pages 317–320. ga95aVahidov. [1053] Dan Ventura, Tim L. Andersen, and Tony R. Martinez. Using evolutionary computation to generate training set data for neural networks. In Pearson et al. [1913], pages 468–471. ga95aVentura. [1054] Francesco Vivarelli, Giuliano Giusti, Marco Villani, Renato Campanini, Piero Fariselli, Mario Compiani, and Rita Casadio. LGANN: a parallel system combining a local genetic algorithm and neural networks for the prediction of secondary structure of protein. Computer Applications in the Biosciences (CABIOS), 11(3):253–260, June 1995. ga95aVivarelli. [1055] E. Vonk, L. C. Jain, L. P. J. Veelenturf, and R. Hibbs. Integrating evolutionary computation with neural networks. In Proceedings of the elektronic Technology Directions to the Year 2000, pages 137–143, Adelaide (Australia), 23.-25. May 1995. IEEE Computer Society Press, Los Alamitos, CA. †EEA 45018/95 ga95aVonk. [1056] Raul Sidnei Wazlawick and Antonio Carlos da Rocha Costa. Non-supervised sensory-motor agents learning. In Pearson et al. [1913], pages 49–52. ga95aWazlawick. [1057] L. Wehenkel, I. Houben, and M. Pavella. Automatic learning approaches for on-line transient stability preventive control of the Hydro-Quebec system. II. a toolbox combining decision trees with neural nets and nearest neighbor classifiers optimized by genetic algorithms. In ?, editor, A Proceedings volume from the IFAC Symposium, volume ?, pages 391–396, Cancun (Mexico), 6.-8. December 1995. Pergamon, Oxford (UK). †CCA63593/97 ga95aWehenkel. [1058] P. R. Weller, R. Summers, and A. C. Thompson. Using a genetic algorithm to evolve an optimum input set for a predictive neural network. In IEE/IEEE Sheffield ’95 [1918], pages 256–258. †conf.prog ga95aWeller. [1059] P. Wilke, J. Rehder, G. Billing, C. Mansfeld, and J. Nilson. NeuroGraph – a simulation environment for neural networks, genetic algorithms and fuzzy logic. In Pearson et al. [1913], pages 515–518. ga95aWilke. [1060] Weixin Xie, Wenhua Li, and Xinbo Gao. Fuzzy-Kohonen-clustering neural network trained by genetic algorithm and fuzzy competition learning. In Shuzi Yang, Ji Zhou, and Cheng-Gang Li, editors, International Conference on Intelligent Manufacturing, volume SPIE-2620, pages 493–498, ?, August 1995. The International Society for Optical Engineering. * www/SPIE Web ga95aWXie. [1061] Percy P. C. Yip and Yoh-Han Pao. A perfect integration of neural networks and evolutionary algorithms. In Pearson et al. [1913], pages 88–91. ga95aYip. [1062] Katsuhisa Yoshimoto, Keiichiro Yasuda, and Ryuichi Yokoyama. Transmission expansion planning using neuro-computing hybridized with genetic algorithm. In ICEC’95 [1917], pages 126–131. †prog. ga95aYoshimoto. [1063] Yuntao Qiam and Weixin Xie. Training radial basis function classifier with Gaussian kernel clustering and fuzzy technique. In Shuzi Yang, Ji Zhou, and Cheng-Gang Li, editors, International Conference on Intelligent Manufacturing, volume SPIE-2620, pages 503–508, ?, August 1995. The International Society for Optical Engineering. * www/SPIE Web ga95aYQian. 118 Genetic algorithms and neural networks [1064] Raed Abu Zitar and Mohamad H. Hassoun. Neurocontrollers trained with rules extracted by a genetic assisted reinforcement learning system. IEEE Transactions on Neural Networks, 6(4):859–879, July 1995. ga95aZitar. [1065] A. M. Langley, S. A. Barton, and A. B. Markov. Simulated flight control using a hybrid neural network/genetic algorithm architecture. In Proceedings of the Electronic Technology Directions to the Year 2000, pages 150–154, Adelaide, SA (Australia), 23.-25. May 1995. IEEE Computer Society Press, Los Alamitos, CA. †EEA51781/95 ga95bAMLangley. [1066] Tim L. Andersen and Tony R. Martinez. Provably convergent dynamic training method for multi-layer perceptron networks. In Proceedings of the 1995 RNNS/IEEE 2nd International Symposium on Neuroinformatics and Neurocomputers, pages 77–84, Rostov-on-Don (Russia), 20.-23. September 1995. IEEE. †EI M066586/95 ga95bAndersen. [1067] J. Balicki and Z. Kitowski. Multicriteria optimization of computer resource allocations with using genetic algorithms and artificial neural networks. In Proceedings of the 12th International Conference on Systems Science, volume 3, pages 11–18, Wroclaw, Poland, 12.-15. September 1995. Oficyna Wydawnicza Politechniki Wroclawskiej, Wroclaw, Poland. †CCA82717/96 ga95bBalicki. [1068] Jürgen Branke. Evolutionary algorithms in neural network design and training – a review. In Alander [1915], pages 145–164. (ftp://ftp.uwasa.fics/1NWGA/Branke.ps.Z) ga95bBranke. [1069] Chen-Phon Wu and Ching-Shiow Tseng. Function approximation neural network with genetic training algorithms. J. Chin. Soc. Mec. Eng. Trans. Chin. Inst. Eng. Ser. C, 16(4):373–381, 1995. †CCA 31911/96 EI M035003/95 ga95bC-PWu. [1070] Brian Carse, Anthony G. Pipe, Terence C. Fogarty, and Terence Hill. Evolving radial basis function neural networks using a genetic algorithm. In ICEC’95 [1917], pages 300–305. †prog. ga95bCarse. [1071] Sung-Bae Cho. Towards an intelligent system based on fuzzy logic, neural networks and genetic algorithm. In ?, editor, Proceedings of the International Joint Conference of CFSA/IFIS/SOFT ‘95 on Fuzzy Theory and Applications, pages 121–126, Taipei, Taiwan, 7.-9. December 1995. World Scientific, Singapore. * CCA90327/96 ga95bCho. [1072] Li-Der Chou and Jean-Lien C. Wu. Buffer management using genetic algorithms and neural networks. In Proceedings of the IEEE Global Telecommunications Conference, volume 2, pages 1333–1337, Singapore, 13.-17. November 1995. IEEE, New York, NY. †CCA63317/96 ga95bChou. [1073] S. Collins, R. Srikanth, R. George, and N. Warsi. A GA driven neural net for curve fitting. In Proceedings of the First International Conference, volume 1, pages 116–118, Atlanta, GA, 28.-31. May 1995. Dynamic Publishers 1995, Atlanta, GA. †CCA95397/95 ga95bCollins. [1074] C. R. Chow and C. H. Chu. On the configuration of multilayered feedforward networks by an evolutionary process. In Proceedings of the 37th Midwest Symposium on Circuits and Systems, volume 1, pages 531–534, Lafayette, LA, 3.-5. August 1995. IEEE, New York, NY. †CCA783/95 ga95bCRChow. [1075] Chi Yung Fu, Loren Petrich, and Benjamin Law. Application of neural manufacturing concept to process modeling, monitoring and control. In Proceedings of the Spring Meeting of MRS, volume 389, pages 333– 338, San Francisco, CA, 17.-20. April 1995. Materials Research Society, PIttsburg, PA. †EI M202423/95 ga95bCYFu. [1076] T. F. Degener and M. Kunze. Application of a neural network and a genetic algorithm in the analysis of multiparticle final states. Int. J. Mod. Phys. C, Phys. Comput. (Singapore), 6(4):599–604, 1995. †CCA96950/95 ga95bDegener. [1077] David E. Moriarty and Risto Miikkulainen. Discovering complex Othello strategies through evolutionary neural networks. Connection Science, 7(?):195–209, ? 1995. * UTCS lop ga95bDEMoriarty. [1078] Andrej Dobnikar. Evolutionary design of application-specific neural networks: A genetic approach. Neural Network World, 5(1):41–50, 1995. †EI M199146/95 ga95bDobnikar. [1079] Eduardo do Valle Simoes, George Fabris Justo, and Dante Augusto Couto Barone. Novel intelligent environment dedicated to ANN fast prototyping. In Proceedings of the 1995 IEEE International Conference on Systems, Man and Cybernetics, volume 1, pages 863–867, Vancouver, BC (Canada), 22.-25. October 1995. IEEE, Piscataway, NJ. †EI M039635/95 ga95bdoValleSimoes. [1080] Y. M. Enab. Genetic algorithm for identifying selfgenerating radial basis neural networks. In Proceedings of the 4th International Conference on Artificial Neural Networks, pages 65–70, Cambridge, UK, 26.-28. June 1995. IEE, Stevenage (UK). †EI M14872/95 ga95bEnab. Bibliography 119 [1081] C. V. Forst, C. Reidys, and J. Weber. Evolutionary dynamics and optimization: neutral networks as model-landscapes for RNA secondary-structure folding-landscapes. In Proceedings of the Third European Conference on Artificial Life, pages 128–147, Granada (Spain), 4.-6. June 1995. Springer - Verlag 1995, Berlin, Germany. †CCA78898/95 ga95bForst. [1082] Toshio Fukuda, Hideyuki Ishigami, and Fumihito Arai. Cell recognition by neural networks using the genetic algorithm. J. Artif. Neural Netw. (USA), 2(1-2):1–15, 1995. †EEA13824/95 ga95bFukuda. [1083] S. Golukakrishnan, C. Chellappen, and V. Sankaranasayanan. Genetic based topology optimized backpropagation network (OSTOP system) for finger print identification. In Proceedings of the Second Asian Conference on Computer Vision, pages 108–112, Singapore, 5.-8. December 1995. Nanyang Technol. University, Singapore. †CCA 69761/96 ga95bGolukakr. [1084] Gisbert Schneider, Johannes Schuchhardt, and Paul Wrede. Amino acid sequence analysis and design by artificial neural network and simulated molecular evolution – an evaluation. Endocytobiosis and Cell Research, 11(1):1–18, 1995. †[1592] ga95bGSchneider. [1085] Ari Hämäläinen. Geneettiset algorithmit neuroverkkojen opetuksessa ja rakenteen suunnittelussa. In Eero Hyvönen and Jouko Seppänen, editors, Keinoelämä – Artificial Life, pages 201–206, Helsinki (Finland), 12. May 1995. Finnish Artificial Intelligence Society (FAIS), Espoo. (in Finnish) ga95bHamalainen. [1086] G. Herries, A. Murray, Sean Danaher, and Thomas Selige. Classification of remote sensing imagery using genetic algorithms and neural networks. In ?, editor, Proceedings of the 1995 Image and Signal Processing for Remote Sensing II, volume SPIE-2579, pages 200–209, Paris, France, 25. September 1995. Society of Photo-Optical Instrumentation Engineers, Bellingham, WA. †EI M064035/95 ga95bHerries. [1087] Hualou Liang and Guiliang Dai. Combination of genetic algorithms and artificial neural networks: Review and prospect. Tien Tzu Hsueh Pao, 23(10):194–200, 1995. †EI M039562/95 ga95bHLiang. [1088] T. Holter, X. Q. Yao, L. C. Rabelo, A. Jones, and Y. W. Yih. Integration of neural networks and genetic algorithm for an intelligent manufacturing controller. Computers & Industrial Engineering, 29(?), 1995. †P68250 ga95bHolter. [1089] Takumi Ichimura, Takeshi Takano, and Eiichiro Tazaki. Reasoning and learning method for fuzzy rules using neural networks with adaptive structured genetic algorithm. In Proceedings of the 1995 IEEE International Conference on Systems, Man and Cybernetics, volume 4, pages 3269–3274, Vancouver, BC (Canada), 22.-25. October 1995. IEEE, Piscataway, NJ. †EI M039669/95 ga95bIchimura. [1090] Hideyuki Ishigami, Toshio Fukuda, Takanori Shibata, and Fumihito Arai. Structure optimization of fuzzy neural network by genetic algorithm. Fuzzy Sets and Systems, 72(3):257–264, 1995. †CCA51825/95 ga95bIshigami. [1091] P. Ivanova. Feature selection for neural network forecaster by genetic algorithms. In ?, editor, Proceedings of the 12th International Conference on Systems Science, volume 3, pages 402–408, Wroclaw, Poland, 12.15. September 1995. Oficyna Wydawnicza Politechniki Wroclawskiej, Wroclaw, Poland. †CCA84544/96 ga95bIvanova. [1092] V. Jerabek and G. Lachiver. Micro-genetic algorithms in the optimisation of neuro-fuzzy controllers. In 1995 Canadian Conference on Electrical and Computer Engineering, volume 1, pages 109–112, ?, ? 1995. †CCA29856/95 ga95bJerabek. [1093] M. F. Kanevskij. Using of artificial neural networks for the spatial interpolations of radioecological data. Izv. Akad. Nauk. Energ., ?(3):26–33, 1995. †EI M026884/95 ga95bKanevski. [1094] H. Kato, Y. Sugai, and T. Kawase. Prediction of daily maximum electric load by a recurrent neural network using genetic algorithm. Transactions of the Institute of Electrical Engineers of Japan B, 115-B(8):875–882, 1995. †CCA85427/95 ga95bKato. [1095] M. Kilinski and H. Kwasnicka. Application of genetic algorithm to neural networks design. In ?, editor, Proceedings of the 12th International Conference on Systems Science, volume 1, pages 164–168, Wroclaw, Poland, 12.-15. September 1995. Oficyna Wydawnicza Politechniki Wroclawskiej, Wroclaw, Poland. †CCA77812/96 ga95bKilinski. [1096] Peter G. Korning. Training neural networks by means of genetic algorithms working on very long chromosomes. International Journal of Neural Systems, 6(3):299–316, September 1995. ga95bKorning. [1097] Panagiotis Liatsis and Yannis J. P. Goulermas. Minimal optimal topologies for invariant higher-order neural architectures using genetic algorithms. In Proceedings of the 1995 IEEE International Symposium on Industrial Electronics, ISIE95, volume 2, pages 792–797, Athens (Greece), 10.-14. July 1995. IEEE, Piscataway, NJ. †EI M096969/96 ga95bLiatsis. 120 Genetic algorithms and neural networks [1098] Young Hee Lim and Dae Hee Park. Optimization of the fuzzy inference model using the hybrid mechanism of genetic algorithms and neural network. J. Korea Inf. Sci. Soc. (South Korea), 22(5):766–775, 1995. †CCA71650/95 ga95bLim. [1099] Rustom Mamlook and Wiley E. Thompson. Multiple-class identification algorithm using genetic neural networks. In Proceedings of the 1995 Signal Processing, Sensor Fusion, and Target Recognition, volume 2484, pages 681–688, Orlando, FL, 17.-19. April 1995. Society of Photo-Optical instrumentation Engineers, Bellingham, WA. †EI M022177/95 ga95bMamlook. [1100] David J. Montana. Neural network weight selection using genetic algorithms. In Suran Goonatilake and Sukhdev Khebbal, editors, Intelligent Hybrid Systems, pages 85–104. John Wiley & Sons, New York, NY, 1995. †toc ga95bMontana. [1101] Tetsuo Morimoto, Josse De Baerdemaeker, and Yasushi Hashimoto. Optimization of storage system of fruits using neural networks and genetic algorithms. In Proceedings of the 1995 IEEE International Conference on Fuzzy Systems, volume 1, pages 289–294, Yokohama (Japan), 20.-24. March 1995. IEEE, Piscataway, NJ. †EI M163865/95 ga95bMorimoto. [1102] Tomoharu Nagao, Takeshi Agui, and Hiroshi Nagahashi. An automatic GA-based construction of neural networks for motion control of virtual life. Transactions of the Institute of Electronics, Information, and Communication Engineers D-II (Japan), J78D-2(7):1150–1152, 1995. †CCA77151/95 ga95bNagao. [1103] F. S. M. Nobre. Genetic-neuro-fuzzy systems: a promising fusion. In Proceedings of 1995 IEEE International Conference on Fuzzy Systems. The International Joint Conference of the Fourth IEEE International Conference on Fuzzy Systems and The Second International Fuzzy Engineering Symposium, volume 1, pages 259–266, Yokohama (Japan), 20.-24. March 1995. IEEE, New York, NY. †CCA60777/95 ga95bNobre. [1104] Stefano Nolfi and D. Parisi. Learning to adapt to changing environments in evolving neural networks. Technical Report NSAL-95012, National Research Counsil (C. N. R.), Institute of Psychology, Rome, 1995. †[?] ga95bNolfi. [1105] Bojan Novak. Superfast autoconfiguring artificial neural networks and their application to power systems. Electr. Power Syst. Res. Eng. Jpn, 35(1):11–16, 1995. †EI M034288/95 ga95bNovak. [1106] R. G. Ojeda, Fernando M. de Azevedo, and Jorge M. Barreto. Genetic algorithms in the optimal choice of neural networks for signal processing. Midwest Symp Circuits Syst, 2(?):1361–1364, 1995. †EI M129874/96 ga95bOjeda. [1107] G. Oyro and L. K. Hansen. Fitness-functions of genetic algorithms for optimizing neural network topologies. In Proceedings of the Norwegian Signal Processing Symposium, pages 32–37, Stavanger, Norway, 1.-2. September 1995. Hogskolen i Stavanger, Stavanger (Norway). †CCA8064/95 ga95bOyro. [1108] Christiaan Perneel, Jean-Marc Themlin, Jean-Michael Renders, and Marc Acheroy. Optimization of fuzzy expert systems using genetic algorithms and neural networks. IEEE Transactions on Fuzzy Systems, 3(3):300–312, August 1995. ga95bPerneel. [1109] Vincent W. Porto, David B. Fogel, and Lawrence J. Fogel. Alternative neural network training methods. IEEE Expert, 10(3):16–22, June 1995. ga95bPorto. [1110] Qing chun Meng and P. F. Jia. Genetic algorithms and their developments. Journal of Qing Hua University, ?(?):?, ? 1995. †[?] ga95bQ-cMeng. [1111] Steve G. Romaniuk. Practical handbook of genetic algorithms. volume 1, Applications, chapter 3. Construction of neural networks, pages 75–99. CRC Press, Boca Raton, FL, 1995. ga95bRomaniuk. [1112] N. Saravanan and David B. Fogel. Evolving neural control systems. IEEE Expert, 10(3):23–27, June 1995. ga95bSaravanan. [1113] M. Schmidt and T. Stidsen. Using GA to train NN using sharing and pruning. In Proceedings of the Fifth Scandinavian Conference on Artificial Intelligence, pages 145–156, Trondheim (Norway), 29.-31. May 1995. IOS Press 1995, Amsterdam, Netherlands. †CCA26501/96 ga95bSchmidt. [1114] A. Schneider. An adaptive system for generating neural networks using genetic algorithms. In D. W. Ruck S. K. Rogers, editor, Proceedings of the 1st International Conference on Applications and Science of Artificial Neural Networks, volume 2492, page 1220pp, Orlando, FL, 17.-21. April 1995. SPIE – The International Society for Optical Engineering. †P67269 ga95bSchneide. [1115] S. G. Walker and D. M. Alexander. The evolutionary direction of neural complexity. In ?, editor, Proceedings of the Sixth Australian Conference on Neural Networks, pages 5–8, Sydney, NSW (Australia), 6.-8. February 1995. Univ. Sydney, Sydney, NSW, Australia. †CCA26514/96 ga95bSGWalker. Bibliography 121 [1116] A. J. Skinner and J. Q. Broughton. Neural networks in computational materials science. Modell Simul Mater Sci Eng, 3(3):371–390, 1995. †EI M165095/95 ga95bSkinner. [1117] Sangbong Park, Lae-Jeong Park, and Cheol Hoon Park. A neuro-genetic controller for nonminimum phase systems. IEEE Transactions on Neural Networks, 6(5):1297–1300, 1995. †CCA79598/95 ga95bSPark. [1118] S. Yao, C. J. Wei, and Z. Y. He. Optimization of wavelet neural network using evolutionary programming. In ?, editor, Proceedings of International Conference on Neural Network Using Evolutionary Programming, volume 1, pages 313–316, Beijing, China, 30. October-2. November 1995. Publishing House of Electron. Ind, Beijing (China). †CCA26587/96 ga95bSYao. [1119] Toshiyuki Tanaka and C.-H. Chuang. Scheduling of linear controllers for X-29 by neural networks and genetic algorithm. In Proceedings of the AIAA Guidance, Navigation and Control Conference, pages 891– 900, Baltimore, MD, 7.-10. August 1995. American Institute of Aeronautics and Astronautics, Washington, DC. †A95-39698 ga95bTTanaka. [1120] E. Vonk, L. C. Jain, L. P. J. Veelenturf, and R. Johnson. Automatic generation of a neural network architecture using evolutionary computation. In Proceedings of the Electronic Technology Directions to the Year 2000, pages 144–149, Adelaide, SA (Australia), 23.-25. May 1995. IEEE Computer Society Press, Los ALamitos, CA. * CCA 47932/95 ga95bVonk. [1121] Rustom Wamlook and Wiley E. Thompson. Multiple-class identification algorithm using genetic neural networks. In Proceedings of the Signal Processing, Sensor Fusion, and Target Recognition Conference, volume SPIE, pages 681–688, Bellingham, WA, 17.-19. April 1995. Society of Photo-Optical Instrumentation Engineers, Bellingham, WA. †A95-43884 ga95bWamlook. [1122] A. G. Williamson. Refining a neural network credit application vetting system with a genetic algorithm. Journal of Microcomputer Applications, 18(3):261–277, 1995. †CCA7137/96 ga95bWilliamson. [1123] Weixin Xie, Wenhua Li, and Xinbo Gao. Fuzzy-Kohonen-clustering neural network trained by genetic algorithm and fuzzy competition learning. In Proceedings of the International Conference on Intelligent Manufacturing, volume 2620, pages 493–498, Wuhan, China, 10. June 1995. SPIE - Society of PhotoOptical Instrumentation Engineering, Bellingham, WA (USA). †EI M066538/96 ga95bXie. [1124] Yan Chen, M. Narita, and T. Yamada. Nuclear reactor diagnostic system using genetic algorithm (GA)trained neural networks. Electr. Eng. Jpn, 115(5):88–99, 1995. †CCA96933/95 ga95bYChen. [1125] Zhixiong Zhang and Kenneth J. Hintz. Evolving neural networks for video attitude and height sensor. In ?, editor, Proceedings of the 1995 Signal Processing, Sensor Fusion, and Target Recognition IV, volume SPIE-2484, pages 383–393, Orlando, FL, 17.-19. April 1995. Society of Photo-Optical Instrumentation Engineers, Bellingham, WA. †EI M024604/95 ga95bZZhang. [1126] M. Chiaberge, J. J. Merelo, L. M. Reyneri, A. Prieto, and L. Zocca. A comparison of neural networks, linear controllers, genetic algorithms and simulated annealing for real time control. In Proceedings of the European Symposium on Artificial Neural Networks, pages 205–210, Bryssels, Belgium, 20.-22. April 1995. De Facto, Brussels, Belgium. †CCA89017/95 ga95cChiaberge. [1127] David E. Moriarty and Risto Miikkulainen. Learning sequential decision tasks. Technical Report AI95-229, The University of Texas at Austin, Department of Computer Sciences, 1995. * UTCS lop ga95cDEMoriarty. [1128] Toshio Fukuda and Koji Shimojima. Fusion of fuzzy, NN, GA to the intelligent robotics. In Proceedings of the 1995 IEEE International Conference Systems, Man and Cybernetics, volume 3, pages 2892–2897, Vancouver, BC (Canada), 22.-25. October 1995. IEEE, New York, NY. †CCA2205/95 ga95cFukuda. [1129] J. Lis. The synthesis of the ranked neural networks applying genetic algorithm with the dynamic probability of mutation. In J. Mira and F. Sandoval, editors, Proceedings of the International Workshop on Artificial Neural Networks, pages 498–504, Malaga-Torremolinos, 7.-9. June 1995. Springer-Verlag, Berlin (Germany). †P66841 CCA34623/96 ga95cJLis. [1130] Henrik Hautop Lund, Luigi Pagliarini, and Orazio Miglino. Artistic design with genetic algorithms and neural networks. In Alander [1915], pages 97–106. (ftp://ftp.uwasa.fics/1NWGA/Lund3.ps.Z) ga95cLund. [1131] F. J. Marin Martin, S. Sanchez Valencia, and F. Sandoval. Genetic programming: foundations and application on the optimization of neural networks. Informática y Automática (Spain), 28(4):30–44, 1995. (in Spanish) † ga95cMartin. [1132] Mircea Gh. Negoita and D. Mihaila. Intelligent techniques based on genetic evolution with applications to neural networks weights optimization. In ?, editor, Proceedings of the 14th International Congress on Cybernetics, volume ?, pages 955–959, Namur, Belgium, 21.-25. August 1995. Assoc. Int. Cybernetique, Namur, Belgium. †CCA61808/97 ga95cNegoita. 122 Genetic algorithms and neural networks [1133] Michael O. Odetayo and Dipankar Dasgupta. Practical handbook of genetic algorithms. In Chambers [1914], chapter 8. Controlling a dynamic physical system using genetic-based learning methods, pages 173–196. ga95cOdetayo. [1134] Tomasz Ostrowski. Genetic algorithm approach to nonlinear adaptive filtering. Journal of Technical Physics (Poland), 36(1):89–101, January 1995. ga95cOstrowski. [1135] Jan Paredis. Coevolutionary computation. Artificial Life, 2(4):355–375, Summer 1995. ga95cParedis. [1136] F. Takeda, S. Omatu, and S. Onami. Mask optimization by genetic algorithm for a neuro-pattern recognition machine with masks. Transactions of the Institute of System, Control, and Information Engineers (Japan), 8(5):196–203, 1995. (In Japanese) †CCA64407/95 ga95cTakeda. [1137] Darrell Whitley, Frédéric C. Gruau, and Larry Pyeatt. Cellular encoding applied to neurocontrol. In Eshelman [1921], page ? †prog ga95cWhitley. [1138] Liang-Jie Zhang, Yan-Da Li, and Hui-Min Chen. Novel global training algorithm and its convergence theorem for fuzzy neural networks. In Proceedings of the 1995 IEEE International Conference on Neural Networks, volume 2, pages 1001–1006, Perth, Australia, 27. November-1. December 1995. IEEE, Piscataway, NJ. * EI M097135/96 ga95cZhang. [1139] Jürgen Branke. Evolutionary algorithms for neural network design and training. Technical Report 322, University of Karlsruhe, Institut für Angewandte Informatik und Formale Beschreibungsverfahren, 1995. ga95dBranke ⇒ . [1140] Henrik Hautop Lund. Pre-adaptations in populations of neural networks living in a changing environment. Artificial Life, 2(?):179–197, ? 1995. †[1911] ga95dLund. [1141] Tomasz Ostrowski. Nonlinear adaptive filtering: The genetic algorithm approach. PhD thesis, Politechnika Warszawska, Poland, 1995. (University Microfilms International, No. 95-38363) * Ostrowski DAI Vol 56 No 7 ga95dOstrowski. [1142] T. Nagao. Optimization of artificial cellular neural networks using a genetic algorithm. In ?, editor, Proceedings of the 6th International Symposium on IC Technology, Systems & Applications, page ?, Singapore, 6.-8. September 1995. Nanyang Technol. University, Singapore. †P69294 ga95dTNagao. [1143] Xin Yao. Evolutionary artificial neural networks. In A. Kent and J. G. Williams, editors, Encyclopedia of Computer Science and Technology, volume 33, pages 137–170. Marcel Dekker Inc., New York, 1995. †News /Yao ga95dXYao. [1144] Pavel Ošmera. Optimization of neural networks by genetic algorithms. Neural Network World, 5(6):965– 976, 1995. †EI M024682/95 ga95eOsmera. [1145] Koji Shimojima, Yasuhisa Hasegawa, and Toshio Fukuda. Force control by RBF fuzzy neuro with unsupervised learning. Nippon Kikai Gakkai Ronbunshu C Hen, 61(?):3311–3317, 1995. †EI M194917/95 ga95eShimojima. [1146] Xin Yao and Yong Liu. Evolving neural networks for medical applications. In Korea-Australia EC’95 [1920], pages 1–16. ga95eXYao. [1147] Xin Yao and Y. Shi. A preliminary study on designing artificial neural networks using co-evolution. In Proceedings of the IEEE Singapore International Conference on Intelligent Control and Instrumentation (SICICI’95), pages 149–154, Singapore, ? 1995. IEEE Singapore Section. †News /Yao ga95fXYao. [1148] David B. Fogel, Eugene C. Wasson III, and Edward M. Boughton. Evolving neural networks for detecting breast cancer. Cancer Letters, 96(?):49–53, ? 1995. ga95hFogel. [1149] Darrell Whitley. Genetic algorithms and neural networks. In G. Winter, J. Périaux, M. Galán, and P. Cuesta, editors, Genetic Algorithms in Engineering and Computer Science (EUROGEN95), pages 203– 216, Las Palmas (Spain), December 1995. John Wiley & Sons, New York. ga95hWhitley. [1150] David B. Fogel and Peter J. Angeline. A review of efforts combining neural networks and evolutionary computation. In Applications of Artificial Neural Networks, volume 2492, pages 586–589, Orlando, FL, 17.-21. April 1995. The International Society for Optical Engineering, Bellingham, WA. †CCA9870/95 ga95iFogel. [1151] David B. Fogel and Peter J. Angeline. Review of efforts combining neural networks and evolutionary computation. In Steven K. Rogers and Dennis W. Ruck, editors, Applications of Artificial Neural Networks, volume SPIE-2492, pages 586–589, ?, April 1995. The International Society for Optical Engineering. * www/SPIE Web ga95kFogel. Bibliography 123 [1152] Angelo Cangelosi. Il ruolo dello sviluppo nei modelli connessionisti. [The role of biological development in connectionist models]. Giornale Italiano di Psicologia, 23(5):777–800, December 1996. * PsycINFO199707695-002 ga96aACangelosi. [1153] Yuji Aoyagi and Toshiyuki Asakura. A study on traffic sign recognition in scene image using genetic algorithms and neural networks. In Proceedings of the 1996 IEEE 22nd International Conference on Industrial Electronics, Control, and Instrumentation (IECON), volume 3, pages 1838–1843, Taipei (Taiwan), 5.-10. August 1996. IEEE Computer Society Press, Los Alamitos, CA. ga96aAoyagi. [1154] J. A. Apolinário Jr., P. R. S. Mendonca, R. O. Chaves, and L. P. Calôba. Cryptanalysis of speech signals ciphered by TSP using annealed hopfield neural-network and genetic algorithms. In George G. Cameron, M. Hassoun, A. Jerdee, and C. Melvin, editors, Proceedings of the 39th Midwest Symposium on Circuits and Systems, volume I-III, pages 821–826, Ames, IA, 18.-21. August 1996. IEEE, New York, NY. * CCA 65571/97 P74974 ga96aApolinario. [1155] A. D. Arbatli and H. L. Akin. Rule extraction from trained neural networks using genetic algorithms. Nonlinear Analysis-Theory Methods & Applications, 30(3):1639–1648, 1996. †P79154 ga96aArbatli. [1156] Barbro Back, Teija Laitinen, and Kaisa Sere. Neural networks and genetic algorithms for bankruptry predictions. In J. K. Lee, J. Liebowitz, and Y. M. Chae, editors, Critical Technology: Proceedings of the Third World Congress on Expert Systems, volume 1, pages 123–130, Seoul (South Korea), 5.-9. February 1996. Cognizant Communication Corp., Elmsford. * CCA 35063/97 P69301 ga96aBBack. [1157] Jon A. Benediktsson, J. R. Sveinsson, J. I. Ingimundarson, H. S. Sigurdsson, and O. K. Ersoy. Multistage classifiers optimized by neural networks and genetic algorithms. Nonlinear Analysis-Theory Methods & Applications, 30(3):1323–1334, 1996. †P79154 ga96aBenediktsson. [1158] A. Bertoni, P. Campadelli, M. Carpentieri, and G. Grossi. A genetic model and the Hopfield networks. In ?, editor, Proceedings of the Artificial Neural Networks - ICANN 96, volume ?, pages 463–468, Bochum, Germany, 16.-19. July 1996. Springer-Verlag, Berlin. †CCA9505/97 ga96aBertoni. [1159] Cheo-Hyeon Cho and Seong-Gon Kong. Structure optimization of a feedforward neural controller using the genetic algorithm. J. Korea Inst. Telemat. Electron. (South Korea), 33B(12):95–105, 1996. In Korean †CCA54848/97 ga96aC-HCho. [1160] R. Calabretta, R. Galbiati, S. Nolfi, and D. Parisi. Two is better than one: a diploid genotype for neural networks. Neural Process. Lett. (Netherlands), 4(3):149–155, 1996. †CCA44774/97 ga96aCalabretta. [1161] Jean-Yves Carrier, John Litva, Henry Leung, and Titus Lo. Genetic algorithm for multiple target tracking data association. In Michael K. Masten and Larry A. Stockum, editors, Acquisition, Tracking, and Pointing X, volume SPIE-2739, pages 180–190, Orlando, FL, 10.-11. April 1996. The International Society for Optical Engineering, Bellingham, WA. †A96-35348 SPIE/Boston P68447/96 ga96aCarrier. [1162] C. T. Charlton and N. R. Ball. Case retrieval using associative networks. In Parmee and Denham [1922], page ? †conf.prog ga96aCharlton. [1163] M. M. M. Chowdhury and Y. Li. Messy genetic algorithm-based new learning-method for structurally optimized neurofuzzy controllers. In Proceedings of the IEEE International Conference on Industrial Technology, pages 274–278, Shanghai, China, 2.-6. December 1996. IEEE, New York, NY. †P75728 ga96aChowdhury. [1164] P. Cortez, J. Machado, and J. Neves. An evolutionary artificial neural network time series forecasting system. In Proceedings of the IASTED International Conference on Artificial Intelligence, Expert Systems and Neural Networks, pages 278–281, Honolulu, HI, 19.-21. August 1996. IASTED, Anaheim, CA (USA). †CCA54348/97 ga96aCortez. [1165] D. Denaro and D. Parisi. Cultural evolution in a population of neural networks. In ?, editor, Proceedings of the 8th Italian Workshop on Neural Nets, pages 100–111, Salemo, Italy, 23.-25. May 1996. Springer-Verlag, London (UK). †CCA89749/97 ga96aDDenaro. [1166] D. D. Wang and Jinwu Xu. Fault detection based on evolving LVQ neural networks. In Proceedings of the 1996 IEEE International Conference on Systems, Man and Cybernetics, volume 1, pages 255–260, Beijing, China, 14.-17. October 1996. IEEE, Piscataway, NJ. †EI M091972/97 ga96aDDWang. [1167] Antonio Delgado, Luis Puigjaner, K. Sanjeevan, and I. Sole. Hybrid system: neural networks and genetic algorithms applied in nonlinear regression and time series forecasting. In ?, editor, Proceedings of the 12th Sympisium, Computational Statistics, volume ?, pages 217–222, Barcelona, Spain, 26.-30. August 1996. Physica-Verlag, Heidelberg, Germany. †EEA427/97 ga96aDelgado. 124 Genetic algorithms and neural networks [1168] G. Destri. Discrete-time cellular neural network construction through evolution programs. In Proceedings of the 1996 Fourth IEEE International Workshop on Cellular Neural Networks and their Applications, pages 473–478, Seville, Spain, 24.-26. June 1996. IEEE, New York, NY. †CCA26821/97 ga96aDestri. [1169] D. H. Ryu, C. R. Kim, S. W. Kim, T. W. Choi, and J. C. Kim. Motion search region prediction using neural network vector quantization. In Proceedings of the 3rd International Conference on Signal Processing, volume 2, pages 1473–1476, Beijing (China), 14.-18. October 1996. IEEE, New York, NY. †CCA70907/97 ga96aDHRyu. [1170] D. Dumitrescu and I. Stan. Genetic algorithms in neural networks. In A. M. Ramsay, editor, Proceedings of the Artificial Intelligence: Methodology, Systems, Applications, volume ?, page ?, Sozopol, Bulgaria, 18.-20. September 1996. IOS Press, Amsterdam/Ohmsha Ltd, Tokyo. †P73003 ga96aDumitres. [1171] D. Ventura and T. R. Martinez. A general evolutionary/neural hybrid approach to learning optimization problems. In Proceedings of the International Neural Network Society 1996 Annual Meetting, pages 1091–1095, San Diego, CA, 15.-18. September 1996. Lawrence Elrbaum Assoc., Mahwah, NJ (USA). †CCA51136/98 ga96aDVentura. [1172] D. W. Juedes and K. Balakrishnan. Generalized neural networks, computational differentiation, and evolution. In Proceedings of the Computational Differentiation on Techniques, Applications, and Tools, pages 273–285, Santa Fe, NM, 12.-14. February 1996. Philadelphia, PA (USA). †CCA26025/98 ga96aDWJuedes. [1173] R. Dybowski, P. Weller, R. Chang, and V. Gant. Prediction of outcome in critically ill patients using artificial neural network synthesised by genetic algorithm. Lancet, 347(9009):1146–1150, 27. April 1996. †MEDLINE ga96aDybowski. [1174] H. Elsimary. Implementation of neural-network and genetic algorithms for novelty filters for fault-detection. In George G. Cameron, H. Hassoun, and C. Melvin A. Jerdee, editors, Proceedings of the 39th Midwest Symposium on Circuits and Systems, volume I-III, pages 1432–1435, Ames, AI, 18.-21. August 1996. IEEE, New York, NY. †P74974 ga96aElsimary. [1175] Hector Erives and Ramon Parra-Loera. Evolved functional neural networks for system identification. In Ivan Kadar and Vibeke Libby, editors, Signal Processing, Sensor Fusion, and Target Recognition V, volume SPIE-2755, pages 414–421, ?, ? 1996. The International Society for Optical Engineering, Bellingham, WA. * CCA94635/96 ga96aErives. [1176] A. I. Esparcia-Alcazar and K. C. Sharman. Genetic evolution of recurrent neural network architectures. In Proceedings of the International Neural Network Society 1996 Annual Meeting, pages 1059–1062, San Diego, CA, 15.-18. September 1996. Lawrence Erlbaum Assoc, Mahwah, NJ (USA). †CCA51131/98 ga96aEsparcia-Alcazar. [1177] A. Fadda and Marc Schoenaur. Identification by evolutionary recurrent neural nets. Z. Angew. Math. Mech. (Germany), 76(3):421–422, 1996. †CCA401/97 ga96aFadda. [1178] Dario Floreano and Francesco Mondada. Evolution of plastic neurocontrollers for situated agents. In Proceedings of the Fourth International Conference on Simulation of Adaptive Behavior, pages 402–410, North Falmouth, MA (USA), 9.-13. September 1996. MIT Press, Cambridge, MA. †CCA43015/98 ga96aFloreano. [1179] M. Fukumi. A method to design a rotation invariant neural pattern recognition system by a genetic algorithm. Bull. Fac. Eng. Univ. Tokushima (Japan), ?(41):87–94, 1996. (In Japanese) †EEA5439/97 ga96aFukumi. [1180] Elvis Galić and Markus Höhfeld. Improving the generalization performance of multi-layer-perceptrons with population-based incremental learning. In Voigt et al. [1923], pages 740–750. ga96aGalic. [1181] Charles Gaudet. Genetic algorithms for pattern recognition. In Pal and Wang [1924], chapter 10. Genetic programming of logic-based neural networks, page ? †toc ga96aGaudet. [1182] E. S. Gelsema. Diagnostic reasoning based on a genetic algorithm operating in a Bayesian belief network. Pattern Recognition Letters, 17(10):1047–1055, 2. September 1996. ga96aGelsema. [1183] S. Gokulakrishnan, C. Chellappan, and V. Sankaranasayanan. Genetic based topology optimized backpropagation network (OSTOP system) for finger print pattern identification. In Proceedings of the Third World Congress on Expert Systems, volume 2, pages 1231–1238, Seoul (South Korea), 5.-9. February 1996. Cognizant Communications Corp., New York, NY (USA). †CCA30034/97 ga96aGokulakrishnan. [1184] Frédéric C. Gruau, Darrell L. Whitley, and Larry Pyeatt. A comparison between cellular encoding and direct encoding for genetic neural networks. In Koza et al. [1925], page ? †conf.prog ga96aGruau. Bibliography 125 [1185] Géza Tóth, Craig S. Lent, P. Douglas Tougaw, Yuriy Brazhnik, Weiwin Weng, Wolfgang Porod, RueyWen Liu, and Yih-Fang Huang. Quantum cellular neural networks. Superlattices and Microstructures, 20(4):473–478, December 1996. †Academic Press/www ga96aGToth. [1186] Juha Hakkarainen, Anne Jumppanen, Jari Kyngäs, and J. Kyyrö. An evolutionary approach to neural network design applied to sunspot prediction. Report A-1996-3, University of Joensuu, Department of Computer Science, 1996. ga96aHakkarainen. [1187] Seung-Soo Han and G. S. May. Optimization of neural network structure and learning parameters using genetic algorithms. In Proceedings of the Eighth IEEE International Conference on Tools with Artificial Intelligence, pages 200–206, Toulouse, France, 16.-19. November 1996. IEEE Computer Society Press, Los Alamitos, CA. †CCA8295/97 ga96aHan. [1188] Uwe D. Hanebeck. Genetic optimization of fuzzy networks. Fuzzy Sets and Systems, 79(1):59–68, 8. April 1996. * EI M078096/96 ga96aHanebeck. [1189] J. V. Hansen and R. D. Meservy. Learning experiments with genetic optimization of a generalized regression neural network. Decis Support Syst (Netherlands), 18(3-4):317–325, 1996. †CCA94910/96 ga96aHansen. [1190] H. Ito and Tatsumi Furuya. Memory-based neural network and its application to a mobile robot with evolutionary and experience learning. In ?, editor, Proceedings of the First International Conference Evolvable Systems: From Biology to Hardware, pages 234–246, Tsukuba, Japan, 7.-8. October 1996. Springer-Verlag, Berlin (Germany). †CCA70638/97 ga96aHIto. [1191] R. Hochman, T. M. Khoshgoftaar, E. B. Allen, and J. P. Hudepohl. Using the genetic algorithm to build optimal neural networks for faultprone module detection. In Proceedings of the Seventh International Symposium on Software Reliability Engineering, volume ?, pages 152–162, White Plains, NY, USA, 30. October-2. November 1996. IEEE Computer Society Press, Los Alamitos, CA. †CCA4936/97 ga96aHochman. [1192] T. Ichimura, T. Takano, and E. Tazaki. Learning of neural networks using hybrid genetic algorithm. In Proceedings of the Fourth European Congress on Intelligent Techniques and Soft Computing, volume 1, pages 526–530, Aachen (Germany), 2.-5. September 1996. Verlag Mainz, Aachen (Germany). †CCA43033/98 ga96aIchimura. [1193] Tin Ilakovac, Zeljka Perkovic, and Strahil Ristov. The use of genetic algorithms in the optimization of competitive neural networks which resolve the stuck vectors problem. In Koza et al. [1925], page ? †conf.prog ga96aIlakovac. [1194] Akira Imada and Keijiro Araki. Basin of attraction of associative memory as it is evolved by a genetic algorithm. In Proceedings of the Second Online Workshop on Evolutionary Computation (WEC2), pages 41–44, Nagoya (Japan), 4.-22. March 1996. ? ga96aImada. [1195] I. W. Wong, D. C. Lam, a. M. Storey, P. Fong, and D. A. Swayne. Target load for reducing acidification using genetic algorithm approach. In Proceedings of the International Neural Network Society 1996 Annual Meeting, page 932, San Diego, CA (USA), 15.-18. September 1996. Lawrence Elbaum Assoc. (Mahwah, NJ, USA). †CCA56395/98 ga96aIWWong. [1196] Ju-Yeop Choi, Hugh F. VanLandingham, and Stanoje Bingulac. A constructive approach for nonlinear system identification using multilayer perceptrons. IEEE Transactions on Systems, Man, and Cybernetics, 26(2):307–312, April 1996. ga96aJ-YChoi. [1197] I. Jagielska, C. Matthews, and T. Whitfort. The application of neural networks, fuzzy logic, genetic algorithms, and rough sets to automated knowledge asquisition. In Proceedings of the 4th International Conference on Soft Computing, volume 2, pages 565–569, Fukuoka, Japan, sep 30.- oct 5. ? 1996. World Scientific, Singapore. †CCA58335/97 ga96aJagielska. [1198] Nick Jakobi. Encoding scheme issues for open-ended artificial evolution. In Voigt et al. [1923], pages 52–61. ga96aJakobi. [1199] J. B. Golden, E. Garcia, and C. Tibbetts. Genome organization and evolutionary search in the design of neural networks. In ?, editor, Proceedings of the Fifth Annual Conference on Evolutionary Programming, pages 397–404, San Diego, CA (USA), 29. February- 3. March 1996. MIT Press, Cambridge, MA. †CCA103615/97 ga96aJBGolden. [1200] W. M. Jenkins. A neural network trained by genetic algorithm. In Proceedings of the Advances in Computational Structures Technology, volume ?, pages 77–84, Budapest (Hungary), 21.-23. August 1996. Civil Comp. Press, Edingburgh. †CCA17390/97 ga96aJenkins. 126 Genetic algorithms and neural networks [1201] Jinn-Moon Yang, Cheng-Yan Kao, and Jorng-Tzong Horng. Evolving neural induction regular language using combined evolutionary algorithms. In Proceedings of the Ninth International Symposium on Artificial Intelligence in Joint Cooperation with the Sixth International Conference on Industrial Fuzzy Control and Intelligent Systems, pages 162–169, Cancun (Mexico), 12.-15. November 1996. Instituto technologio y de Estudios Superiores de Monterrey, Monterrey (Mexico). †CCA55570/99 ga96aJinn-MoonYang. [1202] Jinwoo Kim and Bernard P. Zeigler. Hierarchical distributed genetic algorithms: A fuzzy logic controller design application. IEEE Expert, 11(3):76–84, June 1996. ga96aJinwooKim. [1203] J. J. Buckley, K. D. Reilly, and K. V. Penmetcha. Backpropagation and genetic algorithms for training fuzzy neural nets. In Proceedings of the Fifth IEEE International Conference on Fuzzy Systems (FUZZIEEE’96), volume 1, pages 2–6, New Orleans, LA, 8.-11. September 1996. IEEE, New York. †P72732 ga96aJJBuckley. [1204] J. Murata, Kazuo Tanaka, and K. Hirasawa. Determination and adaptive alteration of artificial neural network structures by a genetic algorithm with a controlled genotype-phenotype mapping. In Proceedings of the 1996 IEEE International Conference on Systems, Man and Cybernetics, volume 3, pages 1690–1695, Beijing (China), 14.-17. October 1996. IEEE, New York, NY. †CCA18733/97 ga96aJMurata. [1205] M. Kishimoto, K. Sakasai, and K. Ara. Solution of electromagnetic inverse problem using combinational method of Hopfield neural network and genetic algorithm. Journal of Applied Physics, 79(1):1–7, January 1996. ga96aKishimoto. [1206] B. Kloppel and G. Winterer. Relapse prediction with alcoholics: a combined neural network/genetic algorithm approach using EEG. In Proceedings of the Fourth European Congress on Intelligent Techniques and Soft Computing, volume 3, pages 2112–2116, Aachen (Germany), 2.-5. September 1996. Verlag Mainz, Aachen (Germany). †CCA49028/98 ga96aKloppel. [1207] R. Kocjancic, B. Walczak, A. Stergarsek, and M. Gerbec. Optimisation of a biosynthetic process using genetic algorithms on a neural net model. In Proceedings of the International Conference on Engineering Problems with Neural Networks, volume 1, page 83.86, London (UK), 17.-19. June 1996. Syst. Eng. Assoc.,Turku (Finland). †CCA102393/99 ga96aKocjancic. [1208] Joost N. Kok, E. Marchiori, M. Marchiori, and C. Rossi. Evolutionary training of CLP-constrained neural networks. In ?, editor, Proceedings of the 2nd International Conference and Exhibition on Practical Application of Constraint Technology, page ?, London (UK), 24.-26. April 1996. ? †prog ga96aKok. [1209] K. S. Ray and J. Ghoshal. Neuro genetic approach to pattern recognition. In Proceedings of the 4th International Conference on Soft Computing, volume 1, pages 221–224, Fukuoka, Japan, 30. Sep- 5. Oct 1996. World Scientific, Singapore. †CCA54141/97 ga96aKSRay. [1210] M. Kupinski, M. L. Giger, and K. Doi. Optimization of neural-network inputs with genetic algorithms. In Digital Mammography ’96, pages 401–404, 1996. †P74190 ga96aKupinski. [1211] Chiaki Kuroda and Kohei Ogawa. A neural network optimized by a genetic algorithm and its application to job-shop scheduling. In ?, editor, Proceedings of the International Conference EANN’96, pages 471–474, ?, ? 1997. ? †[1453] ga96aKuroda. [1212] Jari Kyngäs and Juha Hakkarainen. Predicting sunspot numbers with evolutionarily optimized neural networks. In Alander [1926], pages 173–182. (ftp://ftp.uwasa.fics/2NWGA/Kyngas.ps.Z) ga96aKyngas. [1213] Lucia Ballerini and G. Valli. Neural networks architecture optimization - a survey. Technical Report 9609/02, University of Florence, Department of Electronic Engineering, 1996. †www /Ballerini ga96aLBallerini. [1214] Li Chen, Donald H. Cooley, and Jianping Zhang. Possibility function-based neural networks: Case study of mathematical analysis. In Bruno Bosacchi and James C. Bezdek, editors, Application of Fuzzy Logic Technology III, volume SPIE-2761, pages 62–75, Orlando, FL, 10.-12. April 1996. The International Society for Optical Engineering, Bellingham, WA. ga96aLChen. [1215] Zhang Liangjie, Li Yanda, and Chen Huimin. A new global learning algorithm for fuzzy neural networks based on modified Quasi-Newton method and genetic searching techniques. Acta Electronica Sinica (China), 24(11):5–11, 1996. (In Chinese) †CCA9478/97 ga96aLiangjie. [1216] Ludmila I. Kuncheva and L. Todorova. Prototype selection for an RBF network by a genetic algorithm. In ?, editor, Proceedings of the International ICSC Symposia on Intelligent Industrial Automation and Soft Computing, volume ?, pages B100–B106, Reading, MA, 26.-28. March 1996. Int. Comput. Sci. Conventions, Millet, Alta. (Canada). †CCA77733/96 ga96aLIKuncheva. Bibliography 127 [1217] Lars A. Ludwig, Friedrich Berk, and Adolf Grauel. Using evolutionary algorithms for the structural optimization of an artificial neural network performing the analysis of electronic nose data. Zeitschrift für Angewandte Mathematik und Mechanik, 76(Suppl. 3):499–500, 1996. (Proceedings of ICIAM/GAMM95 Applied Stochastics and Optimization, Hamburg, July 3.-7., 1995) ga96aLudwig. [1218] Liangjie Zhang, Yanda Li, and Huimin Chen. A new global optimizing algorithm for fuzzy neural networks. International Journal of Electronics, 80(3):393–403, March 1996. ga96aLZhang. [1219] E. P. Maillard and D. Gueriot. Designing an optimal RBF classifier using genetic algorithms. In Proceedings of the International Neural Network Society 1996 Annual Meeting, pages 1054–1058, San Diego, CA, 15.18. September 1996. Lawrence Erlbaum Assoc, Mahwah, NJ (USA). †CCA51130/98 ga96aMaillard. [1220] Roman Malczyk and Aleš Gottvald. Comparison of evolution strategy and back-propagation for estimating parameters of neural network. In Ošmera [1927], pages 71–74. ga96aMalczyk. [1221] M. Mangeas and C. Muller. How to find suitable parametric models using genetic algorithms aplication to feedforward neural networks. In ?, editor, Proceedings of the 12th Symposium in Computational Statistics, volume ?, pages 355–360, Barcelona, Spain, 26.-30 August 1996. Physica-Verlag, Heidelberg (Germany). †CCA397/97 ga96aMangeas. [1222] Falvio D. Marques and John Anderson. Modelling and identification of non-linear unsteady aerodynamic loads by neural networks and genetic algorithms. In ?, editor, Proceedings of the 20th ICAS Congress, volume 1, pages 243–251, Naples, Italy, 8.-13. September 1996. American Institute of Aeronautics and Astronautics, Washington, DC. †A96-40557 ga96aMarques. [1223] Helmut A. Mayer, Reinhold Huber, and Roland Schwaiger. Lean artificial neural networks - regularization helps evolution. In Alander [1926], pages 163–172. (ftp://ftp.uwasa.fics/2NWGA/Mayer.ps.Z) ga96aMayer. [1224] Min Woong Hwang and Jin Young Choi. Evolutionary learning algorithm for projection neural networks. In ?, editor, Proceedings of the First Asia-Pacific Conference Simulated Evolution and Learning, pages 136–145, Taejon (Korea), 9.-12. November 1996. Springer-Verlag, Berlin (Germany). †CCA78977/97 ga96aMinHwang. [1225] Motohide Yoshimura, Syunichiro Oe, and Yasunori Shinohara. Texture segmentation method considering optimum number of segmentation areas by using neural networks. Neural Networks, 3(?):1640–1645, ? 1996. ga96aMotohideYoshimura. [1226] M. Munir-ul, M. Chowdhury, and Yun Li. Messy genetic algorithm based new learning method for structurally optimised neurofuzzy controllers. In Proceedings of the IEEE International Conference on Industrial Technology, pages 274–278, Shanghai, China, 2.-6. December 1996. IEEE, New York, NY. †CCA54767/97 ga96aMunir-ul. [1227] Masahiro Murakawa, Shuji Yoshizawa, Isamu Kajitani, Tatsumi Furuya, Masaya Iwata, and Tetsuya Higuchi. Hardware evolution at function level. In Voigt et al. [1923], pages 62–71. ga96aMurakawa. [1228] Stefano Nolfi. Evolving non-trivial behaviors on real robots: A garbage collecting robot. Technical Report NSAL-96026, National Research Counsil (C. N. R.), Institute of Psychology, Rome, 1996. †[?] ga96aNolfi. [1229] T. Nomura and T. Miyoshi. An adaptive fuzzy rule extraction using hybrid model of the fuzzy selforganizing map and the genetic algorithm with numerical chromosomes. In Proceedings of the 4th International Conference on Soft Computing, volume 1, pages 70–73, Fukuoka, Japan, 30. Sep - 5. Oct 1996. World Scientific, Singapore. †CCA53821/97 ga96aNomura. [1230] Jan Paredis. Coevolutionary life-time learning. In Voigt et al. [1923], pages 72–80. ga96aParedis. [1231] Constantinos S. Pattichis and Christos N. Schizas. Genetic-based machine learning for the assessment of certain nuromuscular disorders. IEEE Transactions on Neural Networks, 7(2):427–439, March 1996. ga96aPattichis. [1232] Alejandro Pazos, Julian Dorado, and Antonino Santos. Detection of patterns in radiographs using ANN designed and trained with the genetic algorithm. In Koza et al. [1925], page ? †conf.prog ga96aPazos. [1233] Anthony G. Pipe, Terence C. Fogarty, and A. Winfield. An experiment in knowledge abstraction from cognitive maps to behaviours. In Parmee and Denham [1922], page ? †conf.prog ga96aPipe. [1234] P. X. Zhang, Zhang Qizhi, Wu Liming, and Sui Zhitong. Optimization of compositions of mgo-b2o3-sio2 slags using artificial neural networks and genetic algorithm. Z. Met.kd. (Germany), 87(1):76–78, 1996. †CCA44623/96 ga96aPXZhang. [1235] Q. F. Zhao. Co-evolutionary learning of neural networks. Journal of Intelligent & Fuzzy Systems, 6(1):83– 90, 1996. †P81724 ga96aQFZhao. 128 Genetic algorithms and neural networks [1236] Qiangfu Zhao and Tatsuo Higuchi. Evolutionary learning of nearest-neighbor MLP. IEEE Transactions on Neural Networks, 7(3):762–767, May 1996. ga96aQZhao. [1237] J. V. Ramasamy and S. Rajasekaran. Artificial neural network and genetic algorithm for the design optimization of industrial roofs — a comparison. Computers & Structures, 58(4):747–755, 1996. ga96aRamasamy. [1238] R. Huber, R. Schwaiger, and H. A. Mayer. On the role of regularization parameters in fitness functions for evolutionary designed artificial neural networks. In Proceedings of the International Neural Network Society 1996 Annual Meeting, pages 1063–1066, San Diego, CA, 15.-18. September 1996. Lawrence Erlbaum Assoc, Mahwah, NJ (USA). †CCA51132/98 ga96aRHuber. [1239] Steve G. Romaniuk. Genetic algorithms for pattern recognition. In Pal and Wang [1924], chapter 9. Learning to learn with evolutionary growth perceptrons, page ? †toc ga96aRomaniuk. [1240] H. Rowlands. A hybrid approach for optimum design using a genetic algorithm and a neural network. In Parmee and Denham [1922], page ? †conf.prog ga96aRowlands. [1241] S. Rudolph. On a genetic algorithm for the selection of optimally generalizing neural network topologies. In Parmee and Denham [1922], page ? †conf.prog ga96aRudolph. [1242] R. W. Smalz and M. Conrad. High level control of evolutionary learning in complex neural architectures: the evolutionary credit apportionment approach. In ?, editor, Proceedings of the Fifth Annual Conference on Evolutionary Programming, pages 197–206, San Diego, CA (USA), 29. February- 3. March 1996. MIT Press, Cambridge, MA. †CCA99048/97 ga96aRWSmalz. [1243] Sung-Bae Cho. Genetic combining multiple neural networks for handwritten numeral recognition. In Proceedings of the 4th International Conference on Soft Computing, volume 2, pages 774–777, Fukuoka, Japan, 30. Sep - 5. Oct 1996. World Scientific, Singapore. †CCA54173/97 ga96aS-BCho. [1244] Sang-Kyung Lee and Dongsig Jang. Translation, rotation and scale invariant pattern recognition using spectral analysis and hybrid genetic-neural-fuzzy networks. Computers & Industrial Engineering, 30(3):511–522, July 1996. * EI M131554/96 ga96aS-KLee. [1245] Seong-Sik Yoon, Joo-Young Park, and Dai-Hee Park. Design of brain-state-in-a-box neural networks using parametrization of solution space and genetic algorithm. J. Korea Inst. Telemat. Electron. (South Korea), 33B(2):178–186, 1996. In Korean †CCA61310/96 ga96aS-SYoon. [1246] Seong-Whan Lee. Off-line recognition of totally unconstrained handwritten numerals using multilayer cluster neural network. IEEE Transactions on Pattern Analysis and Machine Intelligence, 18(6):648–652, 1996. ga96aS-WLee. [1247] M. Sase, Y. Yamagata, and Y. Kosugi. Query-based neural network learning using genetic algorithm. Transactions of the Institute of Electronics, Information, and Communication Engineers D-II (Japan), J79D-II(5):960–968, 1996. In Japanese †CCA56311/96 ga96aSase. [1248] Yuji Sato and Tatsumi Furuya. Coevolution in recurrent neural networks using genetic algorithms. Syst. Comput. Jpn. (USA), 27(5):64–73, 1996. †EI M096987/96 ga96aSato. [1249] A. Scherer and G. Schlageter. Usage of back propagation networks in a CAD/CAM system. In Parmee and Denham [1922], page ? †conf.prog ga96aScherer. [1250] M. Schmidt. A unification of genetic algorithms, neural networks and fuzzy logic: the GANNFL approach. In Proceedings of the International Conference on Artificial Neural Networks - ICANN 96, pages 495–500, Bochum, Germany, 16.-19. July 1996. Springer-Verlag, Berlin (Germany). †CCA9508/97 ga96aSchmidt. [1251] S. A. Sergeev and K. V. Mahotilo. Evolutionary synthesis of dynamical object emulator based on RBF neural network. In Proceedings of the First Online Workshop on Soft Computing (WSC1), pages 31–36, WWW (World Wide Web), 19.-30. August 1996. Nagoya University. ga96aSergeev ⇒ WWW(WorldWideWeb). [1252] S. Sette, L. Boullart, and L. Van Langenhove. Optimising a production process by a neural network/genetic algorithm approach. Engineering Applications of Artificial Intelligence, 9(6):681–689, 1996. †CCA 25670/97 ga96aSette. [1253] Sh.-J. Huang and Ch.-L. Huang. Genetic-based multilayered perceptron for Taiwan power system short-term load forecasting. Electr. Power Syst. Res. Eng. Jpn, 38(1):69–74, 1996. †EI M081229/97 ga96aSh-JHuang. [1254] Yi Shang and Benjamin W. Wah. Global optimization for neural network training. Computer, 29(3):45–54, March 1996. ga96aShang. Bibliography 129 [1255] Jack Sklansky and Mark Vriesenga. Genetic selection and neural modeling of piecewise-linear classifiers. International Journal of Pattern Recognition and Artificial Intelligence, 10(5):587–612, August 1996. ga96aSklansky. [1256] S. Kovacs, G. J. Toth, R. Der, and A. Lorincz. Output sensitive discretization for genetic algorithm with migration. Neural Netw. World (Czech Republic), 6(1):101–107, 1996. †EEA113159/96 ga96aSKovacs. [1257] S. M. Lucas. Evolving neural network learning behaviours with set-based chromosomes. In ?, editor, Proceedings of the 4th European Symposium on Artificial Neural Networks, volume ?, pages 291–296, Bruges, Belgium, 24.-26. April 1996. D Facto, Brussels. †CCA87097/96 ga96aSMLucas. [1258] Martin Šojdr. Heterogeneous neural networks and related problems. In Ošmera [1927], pages 164–169. ga96aSojdr. [1259] S. Patro and W. J. Kolarik. Integrated evolutionary computation neural network quality controller for automated systems. In ?, editor, Proceedings of the Fifth Industrial Engineering Research Conference, volume ?, pages 509–514, Minneapolis, MN, 18.-20. May 1996. Inst. Ind. Eng., Norcross, GA (USA). †CCA71498/97 ga96aSPatro. [1260] Seung-Soo Han and G. S. May. Optimization of neural-network structure and learning parameters using genetic algorithms. In Proceedings of the International Test Conference 1996, volume ?, page ?, Washington, DC, 20.-25. October 1996. IEEE Computer Society Press, Los Alamitos, CA. †P73308 ga96aSSHan. [1261] Sung-Sau So and Martin A. Karplus. Evolutionary optimization in quantitative structure-activity relationship: an application of genetic neural networks. Journal of Medicinal Chemistry, 39(7):1521–1530, 29. March 1996. ga96aSSSo. [1262] W. J. Staszewski, K. Worden, and G. R. Tomlinson. Optimal sensor placement for neural network fault diagnosis. In Parmee and Denham [1922], page ? †conf.prog ga96aStaszewski. [1263] Slawomir W. Stepniewski and Andy J. Keane. Topology design of feedforward neural networks by genetic algorithms. In Voigt et al. [1923], pages 771–780. ga96aStepniewski. [1264] R. Stricker and T. Fleischhauer. Effective optimisation of complex systems using ”neural know-how recycling” from simulation and test, by way of example applied to petrol engine management calibration. In Parmee and Denham [1922], page ? †conf.prog ga96aStricker. [1265] D. Su. Development of artificial neural networks for conceptual design of power transmission systems. In Parmee and Denham [1922], page ? †conf.prog ga96aSu. [1266] H. Takahashi and M. Nakajima. A study of designing feedforward neural networks using genetic algorithms. Transactions of the Institute of Electronics, Information, and Communication Engineers D-II (Japan), J79D-II(11):1920–1928, 1996. In Japanese †CCA9396/97 ga96aTakahashi. [1267] Fumiaki Takeda and Sigeru Omatu. Neuro-recognition method for bills using genetic algorithm. Nippon Kikai Gakkai Ronbunshu C Hen, 62(593):135–140, 1996. †EI M067906/96 ga96aTakeda. [1268] Jun Takeuchi and Yukio Kosugi. Neural network implementation to leak localization problems of pipe networks. Nippon Kikai Gakkai Ronbunshu C Hen, 62(595):936–941, 1996. †EI M111399/96 ga96aTakeuchi. [1269] S. Taraglio and A. Zanela. Cellular neural networks: a genetic algorithm for parameters optimization in artificial vision applications. In Proceedings of the 1996 Fourth IEEE International Workshop on Cellular Neural Networks and their Applications, pages 315–320, Seville, Spain, 24.-26. June 1996. IEEE, New York, NY. †CCA28586/97 ga96aTaraglio. [1270] A. V. Timofeyev. Intelligent control and adaptive neural networks computing. In Parmee and Denham [1922], page ? †conf.prog ga96aTimofeyev. [1271] Takashi Kitaguchi. Parameter updating device for neural network, 1996. (JP patent no. 8129542. Issued May 21 1996) * fi.espacenet.com ga96aTKitaguchi. [1272] T. Nomura and T. Miyoshi. An adaptive fuzzy rule extraction using hybrid model of the fuzzy selforganizing map and the genetic algorithm with numerical chromosomes. Journal of Intelligent & Fuzzy Systems, 6(1):39–52, 1996. †P81724 ga96aTNomura. [1273] Thomas Ragg. Parallelization of an evolutionary neural network optimizer based on PVM. In Parallel Virtual Machine – EuroPVM’96, Proceedings of the Third European PVM Conference, volume 1156 of Lecture Notes in Computer Science, pages 351–354, Munich (Germany), 7.-9. October 1996. SpringerVerlag, Berlin (Germany). †CCA22220/97 ga96aTRagg. [1274] U. A. Perez and E. Sanchez. Neural network structure optimization through online hardware evolution. In Proceedings of the World Congress on Neural Networks, pages 1041–1044, San Diego, CA (USA), 15.18. September 1996. Lawrence Erlbaum Assoc. (Mahwah, NJ, USA). †CCA53160/98 ga96aUAPerez. 130 Genetic algorithms and neural networks [1275] S. P. van Helden, H. Hamersma, and V. J. Geerestein. Genetic algorithms in molecular modeling. In J. Devillers, editor, Genetic Algorithms in Molecular Modeling, chapter Prediction of the progesterone receptor binding of steroids using a combination of genetic algorithms and neural networks, pages 159– 192. Academic Press, 1996. †David E. Clark/bib/unp ga96avanHelden. [1276] Evo Volná. Problem of the neural network architecture. In Ošmera [1927], pages 187–191. ga96aVolna. [1277] R. S. D. Wahidabanu and M. A. P. Selvam. NDE of electrical insulation using genetic algorithm-based artificial neural nets. In C. G. K. Nair, B. Raj, C. R. L. Nurthy, and T. Jayakumar, editors, Proceedings of the 14th World Conference on NTD, volume 1-5, pages 1863–1866, New Delhi, India, 8.-13. December 1996. A a Balkema, Rotterdam. †P74646 ga96aWahidabanu. [1278] J. Wallrafen, P. Protzel, and H. Popp. Genetically optimized neural network classifiers for bankruptcy prediction – an empirical study. In Proceedings of the Twenty-Ninth Hawaii International Conference on System Sciences, volume 2, pages 419–426, Wailea, HI, 3.-6. January 1996. IEEE Computer Society Press, Los Alamitos, CA. †CCA40666/96 ga96aWallrafe. [1279] Paul B. Watta, Mohamad H. Hassoun, and Jerome Meisel. Design of optimal neuro-controllers for the separately excited dc motor using a hybrid genetic algorithm-neural network approach. In Steven K. Rogers and Dennis W. Ruck, editors, Applications and Science of Artificial Neural Networks II, volume SPIE-2760, pages 230–241, ?, ? 1996. The International Society for Optical Engineering, Bellingham, WA. * CCA79595/96 ga96aWatta. [1280] H. Westphal and Stefan Bornholdt. Lithofaces prediction from wireline logs with genetic algorithm and neural networks. Zeitschrift der Deutschen Geologischen Gesellschaft, 147(4):465–474, ? 1996. †Bornholdt /lop ga96aWestphal. [1281] B. A. Whitehead. Genetic evolution of radial basis function coverage using orthogonal niches. IEEE Transactions on Neural Networks, 7(6):1525–1528, 1996. ga96aWhitehea. [1282] Bruce A. Whitehead and Timothy D. Choate. Cooperative-competitive genetic evolution of radial basis function centers and widths for time series prediction. IEEE Transactions on Neural Networks, 7(4):869– 880, 1996. ga96aWhitehead. [1283] F. Wieland and F. Aliev. Neuro-fuzzy-genetic adaptive control system. In Proceedings of the Fourth European Congress on Intelligent Techniques and Soft Computing, volume 2, pages 747–751, Aachen (Germany), 2.-5. September 1996. Verlag Mainz, Aachen (Germany). †CCA44595/98 ga96aWieland. [1284] Xiufeng Wang and Malik Elbuluk. Neural network control of induction machines using genetic algorithm training. In Proceedings of the IEEE Industry Applications 31th IAS Annual Meeting, volume 3, pages 1733–1740, San Diego, CA, USA, 6.-10. October 1996. IEEE, Piscataway, NJ. †EI M024960/97 ga96aXiufengWang. [1285] Y. H. Zhou, Z. H. Zhang, Y. C. Lu, and C. Y. Shi. Multistrategy learning using genetic algorithms and neural networks for pattern-classification. In Proceedings of the Information Intelligence and Systems, pages 1686–1689, Beijing (China), 14.-17. October 1996. IEEE, New York, NY. †P74535 ga96aYHZhou. [1286] Y. Liu and Xin Yao. A population-based learning algorithm which learns both architectures and weights of neural networks. Chinese Journal of Advanced Software Research, 3(1):?, ? 1996. (to appear) †News /Yao ga96aYLiu. [1287] Yasuo Matsuyama. Harmonic competition: a self-organizing multiple criteria optimization. IEEE Transactions on Neural Networks, 7(3):652–668, May 1996. ga96aYMatsuyama. [1288] Y. Sato. Evolutionary algorithms that generate recurrent neural networks for learning chaos dynamics. Transactions of the Information Processing Society of Japan, 37(11):1960–1968, 1996. In Japanese †CCA18505/97 ga96aYSato. [1289] Yao Susu, Wei Chengjian, and He Zhenya. An adaptive fuzzy neural network with evolutionary learning algorithm. In Proceedings of the International Conference on Neural Information Processing, volume 2, pages 845–850, Hong Kong, 24.-27. September 1996. Springer-Verlag, Singapore. †CCA18868/97 ga96aYSusu. [1290] Yun Li and A. Haussler. Artificial evolution of neural networks and its application to feedback control. Artificial Intelligence in Engineering (UK), 10(2):143–152, 1996. †CCA27925/96 ga96aYunLi. [1291] Zhigang Li, Shouren Hu, and Hongyi Lu. Feedforward neural networks design by evolutionary programming. In Proceedings of the Third World Congress on Expert Systems, volume 2, pages 1247–1254, Seoul (South Korea), 5.-9. February 1996. Cognizant Communications Corp., New York (USA). †CCA26871/97 ga96aZhigangLi. Bibliography 131 [1292] Nirwan Ansari, A. Arulambalam, and S. Balasekar. Traffic management of a satellite communication network using stochastic optimization. IEEE Transactions on Neural Networks, 7(3):732–744, 1996. †CCA54328/96 ga96bAnsari. [1293] Yuji Aoyagi and Toshiyuki Asakura. Detection and recognition of traffic sign in scene image using genetic algorithms and neural networks. In Proceedings of the 1996 35th SICE Annual Conference, SICE496, pages 1343–1348, Tottori, Japan, 24.-26. July 1996. Society of Instrument and Control Engineers (SICE), Tokyo (Japan). †EI M009243/97 ga96bAoyagi. [1294] Diego Arjona, Rodney K. Lay, and Robert J. Harrington. Hybrid artificial neural network/genetic algorithm approach to on-line switching operations for the optimization of electrical power systems. In Proceedings of the 1996 31st Intersociety Energy Conversion Engineering Conference, IECEM 96, volume 4, pages 2286–2290, Washington, DC (USA), 11.-16. August 1996. IEEE, Piscataway, NJ. †EI M004172/97 ga96bArjona. [1295] Byoung-Tak Zhang. Design and training of neural network models by genetic programming. J. KISS(B), Softw. Appl. (South Korea), 23(10):1083–1092, 1996. In English †EEA14832/97 ga96bB-TZhang. [1296] Shumeet Baluja. Evolution of an artificial neural network based autonomous land vehicle controller. IEEE Transactions on Systems, Man, and Cybernetics, 26(3):450–463, 1996. ga96bBaluja. [1297] Barbro Back, Teija Laitinen, and Kaisa Sere. Neural networks and genetic algorithms for bankruptry prediction. Expert Syst. Appl. (UK), 11(4):407–413, ? 1996. * CCA 15712/97 ga96bBBack. [1298] George Bebis, Michael Georgiopoulos, and T. Kasparis. Coupling weight elimination and genetic algorithms. In Proceedings of the 1996 IEEE International Conference on Neural Networks, volume 2, pages 1115–1120, Washington, DC, 3.-6. June 1996. IEEE, New York, NY. †CCA 86895/96 ga96bBebis. [1299] J. A. Biles, Peter G. Anderson, and Laura W. Loggi. Neural network fitness functions for a musical IGA. In Kevin Warwick, editor, Proceedings of the International ICSC Symposia on Intelligent Industrial Automation and Soft Computing, pages B39–44, Reading, UK, 26.-28. March 1996. Int. Comput. Sci. Conventions, Millet, Alta. †CCA85988/96 ga96bBiles. [1300] Abdul Rahman Bohari and Naoki Mizuno. Learning and structural design of feedforward neural networks by employing genetic algorithms. In Proceedings of the 1996 35th SICE Annual Conference, SICE’96, pages 1377–1382, Tottori, Japan, 24.-26. July 1996. Society of Instrument and Control Engineers (SICE), Tokyo (Japan). †EI M004923/97 ga96bBohari. [1301] Heinrich Braun. On optimizing large neural networks (multilayer perceptrons) by learning and evolution. Zeitschrift für Angewandte Mathematik und Mechanik, 76(Suppl. 1):211–214, 1996. (Proceedings of ICIAM/GAMM95 Applied Stochastics and Optimization, Hamburg, July 3.-7., 1995) ga96bBraun. [1302] Brian Carse and Terence C. Fogarty. Tackling the “curse of dimensionality” of radial basis functional neural networks using a genetic algorithm. In Voigt et al. [1923], pages 710–719. ga96bCarse. [1303] R. Chentouf and C. Jutten. Combining sigmoids and radial basis functions in evolutive neural architectures. In Proceedings of the 4th European Symposium on Artificial Neural Networks, ESANN ’96, pages 129–134, Bruges, Belgium, 24.-26. April 1996. De Facto, Brussels. †CCA87084/96 ga96bChentouf. [1304] Zhou Chunguang, Zhang Bing, Cheng Yanfeng, and Hu Chengquan. Genetic algorithm and its application in training feedforward neural network. Mini-Micro Syst. (China), 17(6):54–58, 1996. (In Chinese) †CCA77365/96 ga96bChunguan. [1305] Devesh Patel. Using genetic algorithms to construct a network for financial prediction. In ?, editor, Applications of Artificial Neural Networks in Image Processing, volume SPIE-2664, pages 204–213, San Jose, CA, 1. -2. February 1996. The International Society for Optical Engineering, Bellingham, WA. * CCA 58306/96 ga96bDPatel. [1306] T. Drabe, W. Bressgott, and E. Bartscht. Genetic task clustering for modular neural networks. In Proceedings of the International Workshop on Neural Networks for Identification, Control, Robotics, and Signal/Image Processing, pages 339–347, Venice (Italy), 21.-23. August 1996. IEEE Computer Society Press, Los Alamitos , CA. †CCA87103/96 ga96bDrabe. [1307] S. Dreiseitl. Modeling of discrete dynamical systems by neural networks and genetic algorithms. In Proceedings of the Thirteenth European Meeting on Cybernetics and Systems Research, volume 1, pages 89– 94, Vienna, Austria, 9.-12. April 1996. Austrian Soc. Cybernetic Studies, Vienna, Austria. †CCA86634/96 ga96bDreiseitl. [1308] M. A. El-Sharkawi and Shyh-Jier Huang. Development of genetic algorithm embedded Kohonen neural network for dynamic security assessment. In Proceedings of the International Conference on Intelligent Systems Applications to Power Systems, pages 44–49, Orlando, FL, 28. January-2. February 1996. IEEE, New York, NY. †EEA59086/96 ga96bEl-Sharkawi. 132 Genetic algorithms and neural networks [1309] Anna I. Esparcia Alcázar and Ken C. Sharman. Genetic programming techniques that evolve recurrent neural network architectures for signal processing. In Proceedings of the 1996 IEEE Signal Processing Society Workshop, pages 139–148, Kyoto (Japan), 4.-6. September 1996. IEEE, New York, NY. †CCA 90073/96 ga96bEsparcia. [1310] M. Fukumi, S. Omatsu, and Y. Nishikawa. A method to design a neural network by the genetic algorithm with partial fitness. Transactions of the Institute of System, Control, and Information Engineers (Japan), 9(3):74–81, 1996. †CCA43797/96 ga96bFukumi. [1311] Ling Guan. An optimal neuron evolution algorithm for constrained quadratic programming in image restoration. IEEE Transactions on Systems, Man, and Cybernetics, A, Systems Humans, 26(4):513–518, July 1996. ga96bGuan. [1312] Didier Gueriot and Eric Maillard. A local approach for a fuzzy error function used in multilayer perceptron training through genetic algorithm. In Proceedings of the 1996 IEEE International Conference on Neural Networks, volume 2, pages 1050–1055, Washington, DC, 3.-6. June 1996. IEEE, New York, NY. * CCA87188/96 ga96bGueriot. [1313] Heung Bum Kim, Sung Hoon Jung, Tag Gon Kim, and Kyu Ho Park. Fast learning method for backpropagation neural network by evolutionary adaptation of learning rates. Neurocomputing (Netherlands), 11(1):101–106, 1996. †CCA61237/96 ga96bHBKim. [1314] G. Herries, A. Murray, Sean Danaher, and Thomas Selige. Classification of remote sensing imagery using genetic algorithms and neural networks. In Proceedings of the Image and Signal Processing for Remote Sensing, volume SPIE-?, pages 200–209, Bellingham, WA, 25.-27. September 1996. Society of Photo-Optical Instrumentation Engineers, Bellingham, WA. †A96-23200 ga96bHerries. [1315] James P. Ignizio and James R. Soltys. Simultaneous design and training of ontogenic neural network classifiers. Computers & Operations Research, 23(6):535–546, 1996. ga96bIgnizio. [1316] Jong-Hwan Kim and Chi-Ho Lee. Evolutionary ordered neural network and its application to robot manipulator control. In Proceedings of the 1996 IEEE 22nd International Conference on Industrial Electronics, Control, and Instrumentation (IECON), volume 2, pages 876–880, Taipei (Taiwan), 5.-10. August 1996. IEEE Computer Society Press, Los Alamitos, CA. ga96bJ-HKim. [1317] Jinwoo Kim and Bernard P. Zeigler. Designing fuzzy logic controllers using a multiresolutional search paradigm. IEEE Transactions on Fuzzy Systems, 4(3):213–226, August 1996. ga96bJinwooKim. [1318] Kun Hsiang Wu, Chin Hsing Chen, and Jiann Der Lee. Cache-genetic-based modular fuzzy neural network for robot path planning. In Proceedings of the 1996 IEEE International Conference on Systems, Man and Cybernetics, volume 4, pages 3089–3094, Beijing, China, 14.-17. October 1996. IEEE, Piscataway, NJ. ga96bKHWu. [1319] Taek-Beom Koh, Sang-Yeob Cha, Jung-Shik Yu, Kwang-Bang Woo, Dae-Sik Mun, Kyuh-Wan Guak, Jeong-Gon Kim, and Seung-Ho Chang. Modeling and optimal control input tracking using neural network and genetic algorithm in plasma etching process. Transactions of the Korean Insttute of Electrical Engineers (South Korea), 45(1):113–122, 1996. (In Korean) †CCA63081/96 ga96bKoh. [1320] J. Kyngäs and J. Valjakka. Evolutionary neural networks in quantitative structure-activity relationships of dihydrofolate reductase inhibitors. Quantitative Structure-Activity Relationships, 15(?):296–301, ? 1996. †David E. Clark/bib ga96bKyngas. [1321] L. A. Ludwig, A. Grauel, and F. Berk. Genetic generation of novel neural network topologies. In Proceedings of the Fourth European Congress on Intelligent Techniques and Soft Computing, volume 1, pages 521–525, Aachen (Germany), 2.-5. September 1996. Verlag Mainz, Aachen (Germany). †CCA43032/98 ga96bLALudwig. [1322] Lisa A. Meeden. An incremental approach to developing intelligent neural network controllers for robots. IEEE Transactions on Systems, Man, and Cybernetics, 26(3):474–485, 1996. ga96bMeeden. [1323] S. Murnion, J. E. Price, and A. Harget. Resource allocation using genetic and neural algorithms. In ?, editor, Proceedings of the 1st International Conference on GeoComputation, volume 2, pages 649–660, Leeds (UK), 17.-19. September 1996. Univ. Leeds, UK. †CCA18034/97 ga96bMurnion. [1324] ?, editor. Computer simulation gaming systems utilizing neural networks and genetic algorithms, volume SPIE-2760, ?, ? 1996. SPIE. †CCA 86004/96 ga96bNorioBaba. [1325] Wang Qiang, Shao Huihe, and Zhang Zhongjun. Genetic evolved neural network and its application in formaldehyde process modeling and optimization. J. Shanghai Jiaotong Univ. (China), 30(4):143–150, 1996. (In Chinese) †CCA88573/96 ga96bQiang. Bibliography 133 [1326] Shyh-Jier Huang. Power system unit commitment using genetic-based neural networks. J. Chin. Inst. Eng. Trans. Chin. Inst. Eng. Ser. A, 3(1):87–96, 1996. †EI M092204/96 ga96bS-JHuang. [1327] Seung-Soo Han and Gary S. May. Recipe synthesis for PECVD SiO2 films using neural networks and genetic algorithms. In Proceedings of the 1996 IEEE 46th Electronic Components & Technology Conference, ETCT, pages 855–860, Orlando, FL, 28.-31. May 1996. IEEE, Piscataway, NJ. †EI M138958/96 ga96bS-SHan. [1328] Sungshin Kim and George J. Vachtsevanos. Polynomial fuzzy neural network for identification and control. In Proceedings of the 1996 Biennial Conference of the North American Fuzzy Information Processing Society - NAFIPS, pages 5–9, Berkeley, CA, 19.-22. June 1996. IEEE, Piscataway, NJ. * EI M142775/96 ga96bSKim. [1329] Shane Murnion, Jason E. Price, and Alan Harget. Resource allocation using genetic and neural algorithms. In ?, editor, Extended Abstracts from the 1st International Conference on GeoComputation, page ?, Leeds (UK), 17.-19 September 1996. GeoComputation CD-ROM. * www ga96bSMurnion. [1330] Sung-Sau So and Martin A. Karplus. Genetic neural networks for quantitative structure-activity relationship: Improvements and application of benzodiazepine affinity for benzodiazepine/GABA(A) receptors. Journal of Medicinal Chemistry, 39(26):5246–5256, 20. December 1996. ga96bSSSo. [1331] Taek-Beom Koh, Sang-Yeob Cha, Jung-Shik Yu, Kwang-Bang Woo, Dae-Sik Mun, Kyuh-Wan Guak, Jeong-Gon Kim, and Seung-Ho Chang. Modeling and optimal control input tracking using neural network and genetic algorithm in plasma etching process. Transactions on Korean Insttute of Electrical Engineers (South Korea), 45(1):113–122, 1996. In Korean †CCA63081/96 ga96bT-BKoh. [1332] Xin Yao and Yong Liu. Evolving artificial neural networks through evolutionary programming. In ?, editor, Proceedings of the Fifth Annual Conference on Evolutionary Programming, pages 257–266, San Diego, CA (USA), 29. February- 3. March 1996. MIT Press, Cambridge, MA. †CCA99049/97 ga96bXinYao. [1333] Zhaohui Zhang, Yuanhui Zhou, Yuchang Lu, and Bo Zhang. Extracting rules from a GA-pruned neural network. In Proceedings of the 1996 IEEE International Conference on Systems, Man and Cybernetics, volume 3, pages 1682–1685, Beijing (China), 14.-17. October 1996. IEEE, New York, NY. †CCA18732/97 ga96bZZhang. [1334] David W. Coit and Alice E. Smith. Solving the redundancy allocation problem using a combined neural network/genetic algorithm approach. Computers & Operations Research, 23(6):515–526, 1996. ga96cCoit. [1335] Minoru Fukumi and N. Akamatsu. A method to design a neural pattern recognition system by using a genetic algorithm with partial fitness and a deterministic mutation. In Proceedings of the 1996 IEEE International Conference on Systems, Man and Cybernetics, volume 3, pages 1989–1993, Beijing, China, 14.-17. October 1996. IEEE, New York, NY. †CCA22215/97 ga96cFukumi. [1336] Jean-Yves Potvin, D. Dube, and C. Robillard. A hybrid approach to vehicle routing using neural networks and genetic algorithms. Appl. Intell., Int. Artif. Intell. Neural Netw. Complex Probl.-Solving Technol. (Netherlands), 6(3):241–252, 1996. †CCA35397/97 ga96cJ-YPotvin. [1337] M. Fukumi, T. Yoshino, and N. Akamatsu. Designing a neural-network using a genetic algorithm with deterministic mutation and partial fitness. Journal of Intelligent & Fuzzy Systems, 6(1):17–26, 1996. †P81724 ga96cMFukumi. [1338] Qiangfu Zhao and Tatsuo Higuchi. Efficient learning of NN-MLP based on individual evolutionary algorithm. Neurocomputing (Netherlands), 13(2-4):201–215, 1996. †EI M009225/97 ga96cQZhao. [1339] Seung-Soo Han and Gary S. May. Using neural-network process models to perform pecvd silicon dioxide recipe synthesis via genetic algorithms. IEEE Transactions on Semiconductor Manufacturing, 10(2):279– 287, 1996. †P75219 ga96cS-SHan. [1340] Sandeep Jain, Pei-Yuan Peng, Anthony Tzes, and Farshad Khorrami. Neural network design with genetic learning for control of a single link flexible manipulator. Journal of Intelligent Robotic Systems, 15(2):135– 151, February 1996. †EI M066620/96; ei TKKele ga96cSJain. [1341] Brian Carse and Terence C. Fogarty. Fast evolutionary learning of minimal radial basis function neural networks using a genetic algorithm. In Terence C. Fogarty?, editor, Evolutionary Computing, Proceedings of the AISB96 Workshop, pages 18–33, Brighton, UK, 1.-2. April 1996. Springer-Verlag, Berlin (Germany). ga96dCarse. [1342] Qiangfu Zhao. A study on co-evolutionary learning of neural networks. In ?, editor, Proceedings of the First Asia-Pacific Conference, Simulated Evolution and Learning, pages 116–125, Taejon (Korea), 9.-12. November 1996. Springer-Verlag, Berlin (Germany). †CCA79343/97 ga96dQiangfuZhao. 134 Genetic algorithms and neural networks [1343] Shyh-Jier Huang and Ching-Lien Huang. Static security assessment of a large-scale power system using genetic-enhanced neural network approaches. Proceedings of the National Science Council, Republic of China, Part A: Physical Science and Engineering, 20(2):228–235, March 1996. ga96dS-JHuang. [1344] Brian Carse and Terence C. Fogarty. Fast evolutionary learning of minimal radial basis function neural networks using a genetic algorithm. In ?, editor, Proceedings of the Evolutionary Computing, volume ?, pages 1–22, Brighton, UK, 1.-2. April 1996. Springer-Verlag, Berlin (Germany). †CCA94886/96 ga96fCarse. [1345] Q. Wang, H. H. Shao, and Z. J. Zhang. Genetic evolved neural network for process modelling and optimization. In Proceedings of the 13th World Congress, pages 283–288, San Francisco, CA, 30. jun- 5. jul ? 1996. Pergamon, Oxford (UK). †CCA68074/98 ga96fQWang. [1346] A. D. Brown and H. C. Card. Evolutionary artificial neural networks for competitive learning. In Proceedings of the 1997 IEEE International Conference on Neural Networks, volume 3, pages 1558–1562, Houston, TX, 9.-12. June 1997. IEEE, New York, NY. †CCA79080/97 ga97aADBrown. [1347] J. Aguilar and A. Colmenares. Recognition algorithm using evolutionary learning on the random neural networks. In Proceedings of the 1997 IEEE International Conference on Neural Networks, volume 2, pages 1023–1028, Houston, TX, 9.-12. June 1997. IEEE, New York, NY. †CCA79366/97 ga97aAguilar. [1348] A. Hunter, G. Hare, and K. Brown. Genetic design of real-time neural network controllers. Neural Comput. Appl. (UK), 6(1):1055–1061, 1997. †CCA100864/97 ga97aAHunter. [1349] A. J. F. Van Rooij, L. C. Jain, and R. P. Johnson. Neural Network Training Using Genetic Algorithms. Machine Perception and Artificial Intelligence. World Scientific Publishers Co., Singapore, 1997. †www.amazon.com ga97aAJFVanRooij. [1350] Abraham Kandel, Yan-Qing Zhang, and H. Bunke. A genetic fuzzy neural network for pattern recognition. In Proceedings of the Sixth IEEE Internatonal Conference on Fuzzy Systems, volume 1, pages 75–78, Barcelona (Spain), 1.-5. July 1997. IEEE, New York, NY. †CCA79454/97 ga97aAKandel. [1351] A. M. Alimi. An evolutionary neuro-fuzzy approach to recognize on-line Arabic handwriting. In Proceedings of the Fourth International Conference on Document Analysis and Recognition, volume 1, pages 382–386, Ulm, Germany, 18.-20. August 1997. IEEE Computer Society Press, Los Alamitos , CA. †CCA90179/97 ga97aAMAlimi. [1352] J. A. Apolinário Jr., P. R. S. Mendoça, R. O. Chaves, and L. P. Calôba. Cryptanalysis of speech signals ciphered by TSP using annealed Hopfield neural network and genetic algorithms. In Proceedings of the 1997 39th Midwest Symposium on Circuits and Systems, volume 2, pages 821–824, Ames, Iowa, 18.-11. August 1997. IEEE, Piscataway, NJ. ga97aApolinario. [1353] A. P. Topchy and O. A. Lebedko. Neural network training by means of cooperative evolutionary search. Nucl. Instrum. Methods Phys. Res. A, Accel. Spectrom. Detect. Assoc. Equip. (Netherlands), 389(1-2):240– 241, 1997. †CCA78887/97 ga97aAPTopchy. [1354] K. Arai and E. Aiyoshi. A hybrid learning algorithm integrating genetic algorithms with neural networks for saccade generation model. Trans. Inst. Electr. Eng. Jpn. C (Japan), 117-C(2):150–157, 1997. In Japanese †CCA44958/97 ga97aArai. [1355] A. R. Burton and T. Vladimirova. Utilisation of an adaptive resonance theory neural network as a genetic algorithm fitness evaluator. In Proceedings of the 1997 IEEE International Symposium on Information Theory, page 209, Ulm, Germany, 29. jun- 4. jul ? 1997. IEEE, New York, NY. †CCA29266/98 ga97aARBurton. [1356] A. Ribert, E. Stocker, Y. Lecourtier, and A. Ennaji. Optimizing a neural network architecture with an adaptive parameter genetic algorithm. In Proceedings of the International Work-Conference on Artificial and Natural Neural Networks, volume ?, pages 527–535, Lanzarote, Spain, 4.-6. June 1997. Springer-Verlag, Berlin (Germany). †CCA78960/97 ga97aARibert. [1357] J. Balicki, A. Stateczny, and B. Zak. Genetic algorithms and Hopfield neural networks for solving combinatorial problems. Appl. Math. Modelling, 7(3):567–592, 1997. †CCA12397/98 ga97aBalicki. [1358] R. Baumgart-Schmitt, W. M. Herrmann, R. Eilers, and F. Bes. On the use of neural network techniques to analyse sleep EEG data. first communication: application of evolutionary and genetic algorithms to reduce the feature space and to develop classification rules. Neuropsychobiology, 36(?):194–210, ? 1997. †[1840] ga97aBaumgart-Schmitt. [1359] B. Chandler, C. Rekeczky, Y. Nishio, and A. Ushida. Using adaptive simulated annealing in CNN template learning-a powerful alternative to genetic algorithms. In Proceedings of the 1997 European Conference on Circuit Theory and Design, volume 2, pages 655–660, Budapest (Hungary), 31. aug- 3. sept ? 1997. Tech. Univ. Budabest, Budabest (Hungary). †CCA77477/99 ga97aBChandler. Bibliography 135 [1360] B. Choi, J. McCullagh, and K. Bluff. Optimising rainfall and temperature estimations using genetic selection of the input vector. In Proceedings of the Eighth Australian Conference on Neural Networks, volume ?, pages 30–34, Melbourne, Vic., Australia, 11.-13. June 1997. Telstra Res. Lab., Clayton, Vic., Australia. †CCA87599/97 ga97aBChoi. [1361] Lee A. Belfore, II and Abdul-Rahman A. Arkadan. Modeling faulted switched reluctance motors using evolutionary neural networks. IEEE Transactions on Industrial Electronics, 44(2):226–233, April 1997. ga97aBelfore. [1362] Jon A. Benediktsson, J. R. Sveinsson, J. I. Ingimundarson, H. S. Sigurdsson, and O. K. Ersoy. Multistage classifiers optimized by neural networks and genetic algorithms. Nonlinear Analysis-Theory Methods & Applications, 30(3):1323–1334, December 1997. (Proceedings of Second World Congress on Nonlinear Analysis, Athens (Greece), 10.-17. July 1996) * CCA 13302/98 ga97aBenediktsson. [1363] Bernhard Sendhoff, Clemens Pötter, and Werner von Seelen. The role of information in simulated evolution. In Bar-Yam Yaneer, editor, Unifying themes in complex systems - Proceedings of the International Conference on Complex Systems 1997, volume ?, pages 453–470, ?, September 1997. ? ga97aBSendhoff. [1364] Basilio Sierra and Pedro Larrañaga. Predicting survival in malignant skill melanoma using Bayesian networks automatically induced by genetic algorithms - an empirical-comparison between different approaches. Artificial Intelligence in Medicine, 14(1-2):215, 1997. †P82305 ga97aBSierra. [1365] B. Burdsall and C. Giraud-Carrier. GA-RBF: a self-optimising RBF network. In George D. Smith and Nigel C. Steele, editors, Proceedings of the International Conference on Artificial Neural Networks and Genetic Algorithms, pages 346–349, Norwich, UK, 2.-4. April 1997. ga97aBurdsall. [1366] K. Butchart, N. Davey, and R. G. Adams. An investigation into the performance and representations of a stochastic, evolutionary neural tree. In George D. Smith and Nigel C. Steele, editors, Proceedings of the International Conference on Artificial Neural Networks and Genetic Algorithms, pages 551–554, Norwich, UK, 2.-4. April 1997. ga97aButchart. [1367] Byoung-Tak Zhang, Peter Ohm, and Heinz Mühlenbein. Evolutionary neural trees for modeling and predicting complex systems. Engineering Applications of Artificial Intelligence, 10(5):473–483, October 1997. ga97aByoung-TakZhang. [1368] Chih-Kuan Chiang, Hung-Yuan Chung, and Jin-Jye Lin. A self-learning fuzzy logic controller using genetic algorithms with reinforcements. IEEE Transactions on Fuzzy Systems, 5(3):460–467, August 1997. ga97aC-KChiang. [1369] A. Cangelosi and D. Parisi. A neural network model of caenorhabditis elegans: the circuit of touch sensitivity. Neural Processing Letters, 6(3):91–98, 1997. †PA6581/98 ga97aCangelos. [1370] D. Carreno and X. Ginesta. Facial image recognition using neural networks and genetic algorithms. In ?, editor, Proceedings of the 7th International Conference, CAIP97, pages 605–612, Kiel, Germany, 10.12. September 1997. Springer-Verlag, Berlin. †CCA103389/97 ga97aCarreno. [1371] C. Gegout. Evolutionary learning of recurrent networks by succestive orthogonal inverse approximations. In George D. Smith and Nigel C. Steele, editors, Proceedings of the International Conference on Artificial Neural Networks and Genetic Algorithms, pages 378–383, Norwich, UK, 2.-4. April 1997. Springer-Verlag, Berlin. ga97aCGegout. [1372] Christian Goerick, Berhhard Sendhoff, and Werner von Seelen. From neural networks to neural stratregies. In Proceedings of the International Conference on Acoustics, Speech, and Signal Processing (ICASSP’97), page ?, ?, ? 1997. IEEE Press, Piscataway, NJ. ga97aCGoerick. [1373] Chengyi Sun, Hongxing Chao, and Yan Sun. Genetic-based clustering neural networks and applications. In Proceedings of the 1997 IEEE International Conference on Intelligent Processing Systems, volume 1, pages 439–443, Beijing (China), 28.-31. October 1997. IEEE, New York, NY. †CCA51011/98 ga97aChengSun. [1374] Chen Wenhui, Lei Youkun, and Xie Heng. Short term load forecasting with artificial neural network and genetic algorithms. Autom. Electr. Power Syst. (China), 21(3):29–32, 1997. In Chinese †CCA77379/97 ga97aChenWenhui. [1375] Claudio A. Perez and Carlos A. Holzmann. Improvements on handwritten digit recognition by genetic selection of neural network topology and by augmented training. In Proceedings of the 1997 IEEE International Confeence on Systems, Man, and Cybernetics, volume 2, pages 1487–1491, Orlando, FL, 12.-15. October 1997. IEEE, Piscataway, NJ. †EI M016961/98 ga97aClaPerez. [1376] C. Y. Wu, O. Tsujii, M. T. Freedman, and S. K. Mun. Image feature analysis for classification of microcalfications in digital mammography - neural networks and genetic algorithms. In K. M. Hansen, editor, Proceedings of, volume SPIE-3034, pages 501–509, Newport Beach, CA, 25.-28. February 1997. SPIE – The International Society for Optical Engineering, Bellingham. †P75417 ga97aCYWu. 136 Genetic algorithms and neural networks [1377] David B. Fogel, Eugene C. Wasson III, Edward M. Boughton, V. W. Porto, and J. W. Shively. Initial results of training neural networks to detect breast cancer using evolutionary programming. Control Cybern. (Poland), 26(3):497–510, 1997. †CCA15927/98 ga97aDBFogel. [1378] Hugo De Garis, L. Kang, Q. He, Z. Pan, M. Ootani, and E. Ronald. Million module neural systems evolution - the next step in ATR’s billion neuron artificial brain (“CAM-brain”) project. In ? [1928], pages 335–. †prog ga97aDeGaris. [1379] David E. Moriarty. Symbiotic Evolution of Neural Networks in Sequential Decision Tasks. PhD thesis, The University of Texas at Austin, Department of Computer Sciences, 1997. * UTCS lop ga97aDEMoriarty. [1380] D. McLean, Z. Bandar, and J. D. O’Shea. The evolution of a feedforward neural network trained under backpropagation. In George D. Smith and Nigel C. Steele, editors, Proceedings of the International Conference on Artificial Neural Networks and Genetic Algorithms, pages 518–522, Norwich, UK, 2.-4. April 1997. † ga97aDMcLean. [1381] Domenico Parisi. Cultural evolution in neural networks. †CCA78945/97 ga97aDParisi. IEEE Expert (USA), 12(4):9–14, 1997. [1382] David W. Opitz and Jude W. Shavlik. Connectionist theory refinement: Genetically searching the space of network topologies. Journal of Artificial Intelligence Research, 6(?):177–209, 1997. †C. Ferreira ga97aDWOpitz. [1383] Eduardo Bustillo. A neuro-evolutionary unbiased global illumination algorithm. In J.Dorsey and Ph. Slusallek, editors, Renderin Techniques ’97, Proceedings of the Eurographics Workshop, pages 263–274, St. Etienne (France), 16.-18. June 1997. Springer-Verlag, Berlin. ga97aEBustillo. [1384] E. F. M. Filho and A. Carfalhode. Evolutionary design of MLP neural network architectures. In Proceedings of the 4th Brazilian Symposium on Neural Networks, pages 58–65, Goiania, Brazil, 3.-5. December 1997. IEEE Computer Society Press, Los Alamitos , CA. ga97aEFMFilho. [1385] P. Eggenberger. Creation of neural networks based on developmental and evolutionary principles. In Proceedings of the 7th International Conference, pages 337–342, Lausanne (Switzerland), 8.-10. October 1997. Springer-Verlag, Berlin (Germany). †CCA9572/98 ga97aEggenber. [1386] Hamed Elsimary. Implementation of neural network and genetic algorithms for novelty filter for fault detection. In Proceedings of the 1997 39th Midwest Symposium on Circuits and Systems, volume 3, pages 1432–1435, Ames, Iowa, 18.-11. August 1997. IEEE, Piscataway, NJ. ga97aElsimary. [1387] E. R. Weeks and J. M. Burgess. Evolving artificial neural networks to control chaotic systems. Phys. Rev. E, Stat. Phys. Plasmas Fluids Relat. Interdiscip. Top. (USA), 56(2):1531–1540, 1997. †CCA78899/97 ga97aERWeeks. [1388] Anna J. Esparcia-Alcazar and Ken Sharman. Evolving recurrent neural network architectures by genetic programming. In Koza et al. [1929], page ? †conf.prog ga97aEsparcia-Alcazar. [1389] Felix Heimes, George Zalesski, Walker Land, and Michiharu Oshima. Traditional and evolved dynamic neural networks for aircraft simulation. In Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, volume 3, pages 1995–2000, Orlando, FL, 12.-15. October 1997. IEEE, Piscataway, NJ. †A98-23873 ga97aFeHeimes. [1390] F. J. Marin and F. Sandoval. Electric load forecasting with genetic neural networks. In George D. Smith and Nigel C. Steele, editors, Proceedings of the International Conference on Artificial Neural Networks and Genetic Algorithms, pages 49–52, Norwich, UK, 2.-4. April 1997. Springer-Verlag, Berlin. ga97aFJMarin. [1391] Frank R. Burden, Brendan S. Rosewarne, and David A. Winkler. Predicting maximum bioactivity by effective inversion of neural networks using genetic algorithms. Chemometrics and Intelligent Laboratory Systems, 38(2):127–137, ? 1997. * ChA 12952m/98 ga97aFRBurden. [1392] Kimmo Fredriksson. Genetic algorithms and generative encoding of neural networks for some benchmark classification problems. In Alander [1930], pages 123–134. (ftp://ftp.uwasa.fics/3NWGA/Fredriksson. ps.Z) ga97aFredriksson. [1393] C. M. Friedrich. Using genetic engineering to find modular structures for architectures of artificial neural networks. In George D. Smith and Nigel C. Steele, editors, Proceedings of the International Conference on Artificial Neural Networks and Genetic Algorithms, pages 373–377, Norwich, UK, 2.-4. April 1997. Springer-Verlag, Berlin. ga97aFriedric. [1394] Ch. M. Friedrich and C. Moraga. Using genetic engineering to find modular structures and activation functions for architectures of artificial neural networks. In ?, editor, Proceedings of the International Conference on Computational Intelligence, Lecture Notes in Computer Science, page ?, Dortmund (Germany), 28.-30. April 1997. Springer-Verlag, Berlin. (to appear) †conf. prog. ga97aFriedrich. Bibliography 137 [1395] Fabrizio Russo. Nonlinear filtering of noisy images using neuro-fuzzy operators. In Proceedings of the 1997 International Conference on Image Processing, volume 3, pages 412–415, Santa Barbara, CA (USA), 26.-29. October 1997. IEEE, Los Alamitos, CA. †EI M028438/98 ga97aFRusso. [1396] F. Takeda, T. Nishikage, and S. Omatu. Neural-network recognition system tuned by GA and design of its hardware by DSP. In Proceedings of the Artificial Intelligence in Real-Time Control, pages 319–324, Kuala Lumpur, Malaysia, 22.-25. September 1997. Pergamon Press Ltd., Oxford. †P82895 ga97aFTakeda. [1397] T. Fujii and S. Funabiki. A control strategy of levelling load power fluctuation based on fuzzy-neural network by tuning coefficients of learning rate with genetic algorithm. Transactions of the Institute of Electrical Engineers of Japan D, 117-D(5):552–557, 1997. In Japanese †EEA80053/97 ga97aFujii. [1398] Fu Kai and Xu Wenhua. Training neural network with genetics algorithms for forecasting the stock price index. In Proceedings of the 1997 IEEE International Conference on Intelligent Processing Systems, volume 1, pages 401–403, Beijing (China), 28.-31. October 1997. IEEE, New York, NY. †CCA55420/98 ga97aFuKai. [1399] N. Funabiki, J. Kitamichi, and S. Nishikawa. An evolutionary neural network algorithm for max cut problems. In Proceedings of the 1997 IEEE International Conference on Neural Networks, volume 2, pages 1260–1265, Houston, TX, 9.-12. June 1997. IEEE, New York, NY. †CCA79066/97 ga97aFunabiki. [1400] Fung Jian, Huang Chengjun, and Zhang Min. Neural network design method based on evolutionary programming. J. Shanghai Jiaotong Univ. (China), 31(12):76–81, 1997. (In Chinese) †CCA34279/98 ga97aFungJian. [1401] Takeshi Furuhashi, S. Matsushita, and H. Tsutsui. Evolutionary fuzzy modeling using fuzzy neural networks and genetic algorithm. In Proceedings of 1997 IEEE International Conference on Evolutionary Computation, pages 623–627, Indianapolis, IN, 13.-16. April 1997. IEEE, New York, NY. †CCA 44864/97 ga97aFuruhashi. [1402] T. Furukawa. Inelastic constitutive modeling using genetic algorithms and neural networks. J. Jpn. Soc. Simul. Technol. (Japan), 16(3):166–172, 1997. In Japanese †CCA8284/98 ga97aFurukawa. [1403] G. Bebis, M. Georgiopoulos, and T. Kasparis. Coupling weight elimination with genetic algorithms to reduce network size and preserve generalization. Neurocomputing (Netherlands), 17(3-4):167–194, 1997. †CCA778/98 ga97aGBebis. [1404] F. Gers, Hugo De Garis, and M. Korkin. Codi-1Bit – a simplified cellular-automata based neuron model. In ? [1928], pages 315–334. †prog ga97aGers. [1405] Gopathy Purushothaman and Nicolaos B. Karayiannis. Quantum neural networks (QNN’s). inherently fuzzy feedforward neural networks. IEEE Transactions on Neural Networks, 8(3):679–693, May 1997. ga97aGPurushothaman. [1406] S. Haring, Joost N. Kok, and Michiel C. van Wezel. Feature selection for neural networks through funcional links found by evolutionary computation. In ?, editor, Proceedings of the Second International Symposium on Intelligent Data Analysis (IDA-97), page ?, London (UK), 4.-6. August 1997. ? (to appear: http: //web.dcs.bbk.ac.uk/ida97.html) †conf. prog. ga97aHaring. [1407] P. G. Harrald and M. Kamstra. Evolving artificial neural networks to combine financial forecasts. IEEE Transactions on Evolutionary Computation, 1(1):40–52, 1997. †CCA67540/97 ga97aHarrald. [1408] G. Harrison. Neural networks and genetic algorithms in machinery control-systems. In P. A. Wilson, editor, Proceedings of the Eleventh Ship Control Systems Symposium, volume 1, pages 101–114, Southampton (England), April 1997. Computational Mechanics Publications Ltd, Southampton. †P76028 ga97aHarrison. [1409] K. Hase and N. Yamazaki. Synthesis of bipedal motion resembling actual human walking by neural oscillators and genetic algorithms. Transactions of the Society of Instrument and Control Engineers (Japan), 33(5):448–454, 1997. In Japanese †CCA72753/97 ga97aHase. [1410] Heinrich Braun and Thomas Ragg. Evolutionary optimization of neural networks for reinforsement learning algorithms. In George D. Smith and Nigel C. Steele, editors, Proceedings of the International Conference on Artificial Neural Networks and Genetic Algorithms, pages 384–388, Norwich, UK, 2.-4. April 1997. Springer-Verlag. ga97aHBraun. [1411] H. C. Lee and C. H. Dagli. A parallel genetic-neuro scheduler for job-shop scheduling problems. Int. J. Prod. Econ. (Netherlands), 51(1-2):115–122, 1997. †CCA97794/97 ga97aHCLee. [1412] Hesham A. Hefny, Ashraf H Abdel Wahab, and Samir I. Shaheen. Genetic-based fuzzy neural network (GBFNN), A hybrid approach for approximation. In Blumenstein [1931], pages 122–125. ga97aHefny. 138 Genetic algorithms and neural networks [1413] Tim Hendtlass. Using evolution to develop look up tables for congruent data sets. In Proceedings of the 1997 International Conference on Neural Information Processing and Intelligent Information Systems, volume 1, pages 397–400, Dunedin (New Zealand), 24.-28. November 1997. Springer-Verlag, Singapore. †CCA66691/98 ga97aHendtlass. [1414] Hector Erives and Wiley E. Thompson. Comparative analysis of two evolved neural networks used for the identification and control of a nonlinear plant. In Ivan Kadar, editor, Signal Processing, Sensor Fusion, and Target Recognition VI, volume SPIE-3068, pages 366–373, ?, July 1997. The International Society for Optical Engineering. * www/SPIE Web ga97aHErives. [1415] H. Ezoe and Y. Iwasa. Evolution of condition-dependent dispersal: A genetic-algorithm search for the ESS reaction norm. Researches on Population Ecology, 39(2):127–137, December 1997. * ISI ga97aHEzoe. [1416] Hiroyuki Honda, Taizo Hanai, Takeshi Furuhashi, Yoshiki Uchikawa, and Takeshi Kobayashi. Quality modeling of Ginjo sake by neural network. Proc. World Congr., Int. Fed. Autom. Control, pages 401–406, 1997. †ChA127:32910/97 ga97aHirHonda. [1417] H. Murai, Sigeru Omatu, and S. Oe. Improvement of convergence speed of back-propagation method by genetic algorithm and its application to remote sensing analysis. Transactions of the Institute of Electronics, Information, and Communication Engineers D-II (Japan), J80D-II(5):1311–1313, 1997. In Japanese †CCA65611/97 ga97aHMurai. [1418] H. Murao and S. Kitamura. Evolution of locally defined learning rules and their coordination in feedforward neural networks. Artif. Life Robot. (Japan), 1(2):89–94, 1997. †CCA77486/99 ga97aHMurao. [1419] R. Hochman, T. M. Khoshgoftaar, E. B. Allen, and J. P. Hudepohl. Evolutionary neural networks: a robust approach to software reliability problems. In Proceedings of the Eighth International Symposium on Software Reliability Engineering, volume ?, pages 13–26, Albuquerque, NM, 2.-5. November 1997. IEEE Computer Society Press, Los Alamitos, CA. †CCA5146/98 ga97aHochman. [1420] Huang Xinmin, Wu Zhizheng, and Xu Xiaoming. Linearising feedback of one class of nonlinear system with application of genetic evolved neural network. J. Shanghai Jiaotong Univ. (China), 31(6):38–42, 1997. In Chinese †CCA/91160/97 ga97aHuXinmin. [1421] Heikki Hyötyniemi, Ari S. Nissinen, and Heikki N. Koivo. Evolution based self-organization of structures in linear time-series modeling. In Alander [1930], pages 135–152. (ftp://ftp.uwasa.fics/3NWGA/ Hyotyniemi.ps.Z) ga97aHyotyniemi. [1422] I. Ciuca, J. A. Ware, and A. Cristea. Removing irrelevant features in neural network classification using evolutionary computations. In Proceedings of the Medical Informatics Europe’97, volume 1, pages 391–395, Thessaloniki, Greece, ? 1997. IOS Press, Amsterdam. †CCA84535/98 ga97aICiuca. [1423] I. Harvey. Cognition is not computation; evolution is not optimisation. In Proceedings of the International Conference on Arificial Neural Networks, pages 685–690, Lausanne (Switzerland), 8.-10. October 1997. Springer-Verlag, Berlin (Germany). †CCA9645/98 ga97aIHarvey. [1424] Akira Imada and Keijiro Araki. Application of an evolution strategy to the Hopfield model of associative memory. In Proceedings of 1997 International Conference on Evolutionary Computation, pages 679–683, Indianapolis, IN, 13.-16. April 1997. IEEE, New York, NY. †CCA49123/97 ga97aImada. [1425] M. Ishikawa and K. Nishino. Designing neural networks by a combination of structural learning and genetic algorithms. In Proceedings of the 7th international Conference on Artificial Neural Networks, volume ?, pages 415–420, Lausanne (Switzerland), 8.-10. October 1997. Springer-Verlag, Berlin (Germany). †CCA9584/98 ga97aIshikawa. [1426] Isto Aho, Harri Kemppainen, Kai Koskimies, Erkki Mäkinen, and Tapio Niemi. Searching neural network structures with L systems and genetic algorithms. Report A-1997-15, University of Tampere, Department of Computer Science, 1997. ga97aIstoAho. [1427] I. Jagielska, C. Matthews, and T. Whitfort. A study in experimental evaluation of neural network and genetic algorithm techniques for knowledge aquisition in fuzzy classification systems. In Proceedings of the 1997 IEEE International Conference on Neural Networks, volume 4, pages 2364–2368, Houston, TX, 9.-12. June 1997. IEEE, New York, NY. †CCA84088/97 ga97aJagielsk. [1428] J. Jarmulak, P. Spronck, and J. H. Kerckhoffs. Neural networks in process control: Model-based and reinforcement trained controllers. Computers and Electronics in Agriculture, 18(2-3):149–166, 1997. †BA127077 ga97aJarmulak. [1429] Jose E. Burgos. Evolving artificial neural networks in Pavlovian environments, pages 58–79. NorthHolland/Elsevier Science Publishers, Amsterdam (Netherlands), 1997. * PsycINFO1997-36574-00 ga97aJEBurgos. Bibliography 139 [1430] Jens E. Gayko, Reinhard Lohmann, Heiko Voss, Bernhard Sendhoff, and Thomas Zamzow. Application of structure evolution to sytem state diagnosis. In A. B. Bulsari and S. Kallio, editors, Proceedings of the 1997 International Conference on Engineering Applications of Neural Networks, pages 233–236, Stockholm (Sweden), 16.-18. June 1997. Systeemitekniikan seura ry, Turku (Finland). ga97aJEGayko. [1431] Jeng-Sheng Huang and Hsiao-Chung Liu. Object recognition using genetic algorithms with a Hopfield’s neural model. Expert Systems with Applications, 13(3):191–199, ? 1997. ga97aJeng-ShengHuang. [1432] Jian Fang and Yugeng Xi. Neural network design based on evolutionary programming. Artif. Intell. Eng. (UK), 11(2):155–161, 1997. †CCA 18790/97 ga97aJFang. [1433] Jia Lei, Guangdong He, and Jing Ping Jiang. State estimation of the CSTR system based on a recurrent neural network trained by HGAs. In Proceedings of the 1997 IEEE International Conference on Neural Networks, volume 2, pages 779–782, Houston, TX, 9.-12. June 1997. IEEE, Piscataway, NJ. †EI M178770/97 ga97aJiaLei. [1434] J. Jiang and Darren Butler. Design of an adaptive genetic learning neural network system for image compression. In Proc. of the, volume SPIE-3030, pages 21–28. SPIE - Int. Soc. Opt. Eng. (USA), 1997. †CCA56584/97 ga97aJiang. [1435] Jihoon Yang and Vasant Honavar. Feature subset selection using a genetic algorithm. In Koza et al. [1929], pages 380–399. ga97aJihoonYang. [1436] J. J. Buckley and Yoichi Hayashi. Neural net approximations to solutions of systems of fuzzy linear equations. In Proceedings of the 1997 IEEE International Conference on Neural Networks, volume 4, pages 2355–2358, Houston, TX, 9.-12. June 1997. IEEE, Piscataway, NJ. †EI M174623/97 ga97aJJBuckley. [1437] J. J. Merelo, A. Prieto, F. Moran, R. Marabini, and J. M. Carazo. A GA-optimized neural network for classification of biological particles from electron-microscopy images. In Proceedings of the International Work-Conference on Artificial and Natural Neural Networks, volume ?, pages 1174–1182, Lanzarote, Spain, 4.-6. June 1997. Springer-Verlag, Berlin (Germany). †CCA83479/97 ga97aJJMerelo. [1438] J. M. Molina, A. Berlanga, A. Sanchis, and P. Isasi. Evolving connection weights between sensors and actuators in robots. In Proceedings of the IEEE International on Symposium on Industrial Electronics, volume 2, pages 686–690, Guimaraes, Portugal, 7.-11. July 1997. IEEE, New York, NY. †CCA28256/98 ga97aJMMolina. [1439] J. Neves and P. Cortez. An artificial neural network-genetic based approach for time series forecasting. In Proceedings of the 4th Brazilian Symposium on Neural Networks, pages 9–13, Goiania, Brazil, 3.-5. December 1997. IEEE Computer Society, Los Alamitos , CA. †CCA9679/98 ga97aJNeves. [1440] James V. Hansen and Ray D. Nelson. Neural networks and traditional time series methods: a synergistic combination in state economic forecasts. IEEE Transactions on Neural Networks, 8(4):863–873, July 1997. ga97aJVHansen. [1441] N. K. Kasabov and M. J. Watts. Genetic algorithms for structural optimisation, dynamic adaptation and automated design of fuzzy neural networks. In Proceedings of the 1997 IEEE International Conference on Neural Networks, volume 4, pages 2546–2549, Houston, TX, 9.-12. July 1997. IEEE, New York, NY. †CCA79130/97 ga97aKasabov. [1442] Okyay Kaynak. chapter 107. Application Techniques: Combining fuzzy logic, artificial neural networks, and probabilistic reasoning—soft computing, pages 1360–1363. CRC Press, Boca Raton, FL, 1997. ga97aKaynak. [1443] Michael Kenward. Where to fish for neural nets. Scientific Computing World, ?(32):66, October 1997. ga97aKenward. [1444] Kimmo Fredriksson. Learning the structure of neural networks using genetic algorithms. Master’s thesis, University of Helsinki, Department of Computer Science, 1997. †report on activities ga97aKFredriksson. [1445] K. Fu and W. H. Xu. Training neural-network with genetic algorithms for forecasting thr stock-price index. In Proceedings of the 1997 IEEE International Conference on Intelligent Processing Systems, volume 1-2, pages 401–403, Beijing (China), 28.-31. October 1997. IEEE New York, NY. †P80107 ga97aKFu. [1446] V. V. Kholodovuich. Search for tuftsin-like peptides using computer modeling of the complementarity of amino acids based on the genetic code algorithm. Ukr. Biokhim. Zh., 69(5-6):203–208, ? 1997. (in Russian) * ChA 306036w/99 ga97aKholodovuich. [1447] H. Kinjo, K. Nakazono, and T. Yamamoto. Pattern recognition for time series signals using recurrent neural networks by genetic algorithms. Transactions of the Institute of System, Control, and Information Engineers (Japan), 10(6):304–314, 1997. In Japanese †CCA71010/97 ga97aKinjo. 140 Genetic algorithms and neural networks [1448] M. Klosowski. Application of genetic algorithms and neural networks to hybrid expert system for electronic filter design. Bull. Pol. Acad. Sci. Tech. Sci. (Poland), 45(4):559–572, 1997. †EEA34581/98 ga97aKlosowsk. [1449] Evgeny Kochergov. Using the genetic algorithm and neural network to solve the person identification problem. In Alander [1930], pages 163–172. (ftp://ftp.uwasa.fics/3NWGA/Kochergov.ps.Z) ga97aKochergov. [1450] Michael Korkin, Hugo de Garis, Felix Gers, and Hitoshi Hemmi. “CBM (CAM-brain machine)”: A hardware tool which evolves a neural net module in a fraction of a second and runs a million neuron artificial brain in real time. In Koza et al. [1929], page ? †conf.prog ga97aKorkin. [1451] K. Schmidt and R. Schonfeld. Design of neural network controllers for a 2-mass-oscillator using genetic algotihms and implementation in a real-time environment. In Proceedings of the Algorithms and Architectures for Real-Time Control, pages 37–42, Vilamoura, Portugal, 9.-11. ? 1997. Pergamon Press, Oxford. †P80971 ga97aKSchmidt. [1452] Ludmila I. Kuncheva. Initializing of an RBF network by a genetic algorithm. Neurocomputing (Netherlands), 14(3):273–288, 1997. †CCA34388/97 ga97aKuncheva. [1453] Chiaki Kuroda, Fumiyoshi Goto, and Kohei Ogawa. Optimizing ANN by GA with simulated annealing-like mutation as applied to job-shop scheduling. In A. B. Bulsari and S. Kallio, editors, Proceedings of the 1997 International Conference on Engineering Applications of Neural Networks, pages 317–320, Stockholm (Sweden), 16.-18. June 1997. Systeemitekniikan seura ry, Turku (Finland). ga97aKuroda. [1454] K. W. C. Ku and M. W. Mak. Exploring the effects of Lamarckian and Baldvinian learning in evolving recurrent neural networks. In Proceedings of 1997 IEEE International Conference on Evolutionary Computation, pages 617–621, Indianapolis, IN, 13.-16. April 1997. IEEE, New York, NY. †CCA44863/97 ga97aKWCKu. [1455] M. Kwiesielewicz and M. Tomera. Ship inverse model identification using recurrent neural network and genetic algorithms. In Proceedings of the Fourth International Symposium on Methods and Models in Automation and Robotics, volume 2, pages 529–532, Miewdzyzdroje, Poland, 26.-29. August 1997. Wydawnictwo Uczelniane Politech. Szczecinskiej, Szczecin, Poland. †CCA11588/98 ga97aKwiesielewicz. [1456] Pedro Larrañaga, Cindy M. H. Kuijpers, M. Poza, and R. H. Murga. Decomposing Bayesian networks: triangulation of the moral graph with genetic algorithms. Statistics and Computing, 7(1):19–34, January 1997. ga97aLarranaga. [1457] L. Bull. Model-based evolutionary computing: a neural network and genetic algorithm architecture. In Proceedings of 1997 IEEE International Conferenc eon Evolutionary Computation, pages 611–616, Indianapolis, IN, 13.-16. April 1997. IEEE, New York, NY. †44471/97 ga97aLBull. [1458] L. D. Chou and J. L. C. Wu. Bandwidth allocation in ATM networks using genetic algorithms and neural networks. In Proceedings of the IEEE Global Telecommunications Conference, volume 1-3, pages 962–966, Phoenix, AZ, 3.-8. November 1997. IEEE, New York, NY. †P77844 ga97aLDChou. [1459] A. Likartsis, I. Vlachavas, and Lefteri H. Tsoukalas. A new hybrid neural-genetic methodology for improving learning. In Proceedings of the Ninth IEEE International Conference on Tools with Artificial Intelligence, volume ?, pages 32–36, Newport Beach, CA, 3.-8. November 1997. IEEE Computer Society Press, Los Alamitos, CA. ga97aLikartsi. [1460] Derek A. Linkens and H. Okola Nyongesa. Fuzzy evolutionary computation. In Pedrycz [1932], chapter 2.6 Evolutionary learning in neural fuzzy control systems, pages 200–222. ga97aLinkens. [1461] C. Lursinsap and T. Tanprasert. Fault immunization technique for artificial neural networks. In Proceedings of the 1997 IEEE International Conference on Neural Networks, volume 1, pages 302–307, Houston, TX, 9.-12. June 1997. IEEE, New York, NY. †CCA78925/97 ga97aLursinsa. [1462] C. MacLeod and G. Maxwell. Using embryology as an alternative to genetic algorithms for designing artificial neural network topologies. In George D. Smith and Nigel C. Steele, editors, Proceedings of the International Conference on Artificial Neural Networks and Genetic Algorithms, pages 359–363, Norwich, UK, 2.-4. April 1997. † ga97aMacLeod. [1463] Luis Magdalena and Juan R. Velasco. Fuzzy evolutionary computation. In Pedrycz [1932], chapter 2.8 Evolutionary based learning of fuzzy controllers, pages 249–268. ga97aMagdalena. [1464] Milam Aiken. Artificial neural systems as a research paradigm for the study of group decision support systems. Group Dicision and Negotiation, 6(4):373–382, July 1997. * PsycINFO1997-30171-006 ga97aMAiken. [1465] Eric P. Maillard and Didier Gueriot. RBF neural network, basis functions and genetic algorithms. In Proceedings of the 1997 IEEE International Conference on Neural Networks, volume 4, pages 2187–2190, Houston, TX, 9.-12. June 1997. IEEE, Piscataway, NJ. †EI M178937/97 ga97aMaillard. Bibliography 141 [1466] M. Mangeas and C. Muller. An automatic search of feedforward neural network architecture based on genetic algorithms. application to the short-term load forecasting. In Proceedings of the International Conference on Intelligent System Application to Power Systems, pages 362–366, Seoul (South Korea), 6.-10. July 1997. Korean Inst. Electr. Eng, Seoul (South Korea). †CCA16318/98 ga97aMangeas. [1467] P. Marenbach and M. Brown. Evolutionary versus inductive construction of neurofuzzy systems for bioprocess modelling. In Proceedings of the Second International Conference on Genetic Algorithms in Engineering Systems: Innovations and Applications, pages 320–325, Glasgow (UK), 2.-4. September 1997. IEE, London (UK). †CCA7376/98 ga97aMarenbach. [1468] R. B. Maunder, G. G. Coghill, and Z. A. Salcic. Genetic algorithm optimisation of FPLD circuits synthesis from highlever modular descriptions. In Proceedings of the 1997 International Conference on Neural Information Processing and Intelligent Information Systems, volume 1, pages 678–681, Dunedin (New Zealand), 24.-28. November 1997. Springer-Verlag, Singapore. †CCA78705/98 ga97aMaunder. [1469] J. McCullagh, B. Choi, and K. Bluff. Genetic evolution of a neural networks input vector for meteorological estimations. In Proceedings of the 1997 International Conference on Neural Information Processing and Intelligent Information Systems, volume 2, pages 1046–1049, Dunedin (New Zealand), 24.-28. November 1997. Springer-Verlag, Singapore. †CCA82314/98 ga97aMcCullagh. [1470] Mihail Crucianu. Algorithmes d’évolution pour les réseaux de neurones. Rapport de recherche 187, Ecole d’Ingénieurs en Informatique pour l’Industrie, 1997. (in French) ga97aMCrucianu. [1471] Michiel C. van Wezel, Ágoston E. Eiben, C. M. H. van Kemenade, Joost N. Kok, W. Kosters, and I. G. Sprinkhuizen-Kuyper. Natural solutions to practical problems: an overview of marketing, scheduling and information filtering problems solved by neural and evolutionary techniques. In Proceedings of the Neural Networks: Best Practice in Europe, pages 202–205, Amsterdam, Netherlands, 22. May 1997. World Scientific, Singapore. †CCA60786/99 ga97aMCWezel. [1472] M. Fukumi and N. Akamatsu. Designing a neural-network using evolutionary algorithms with deterministic mutation. In Proceedings of the Artificial Intelligence in Real-Time Control, pages 97–102, Kuala Lumpur, Malaysia, 22.-25. September 1997. Pergamon Press Ltd., Oxford. †P82895 ga97aMFukumi. [1473] Graham Miller. Preventing overfitting of evolved neural networks. In John R. Koza, editor, Genetic Algorithms and Genetic Programming at Stanford 1997, page ?, Stanford, CA, Winter 1997. Stanford University Bookstore. †Koza ga97aMiller. [1474] Ming-Yeong Teo, Li-Pheng Khoo, and Siang-Kok Sim. Application of genetic algorithms to optimise Neocognitron network parameters. Neural Netw. World (Czech Republic), 7(3):293–304, 1997. †CCA93974/97 ga97aMing-Teo. [1475] M. Koppen, M. Teunis, and B. Nickolay. A neural network that uses evolutionary learning. In Proceedings of 1997 IEEE International Conference on Evolutionary Computation, pages 635–639, Indianapolis, IN, 13.-16. April 1997. IEEE, New York, NY. †CCA49050/97 ga97aMKoppen. [1476] Tetsuo Morimoto, Josse De Baerdemaeker, and Yasushi Hashimoto. An intelligent approach for optimal control of fruit-storage process using neural networks and genetic algorithms. Computers and Electronics in Agriculture, 18(2-3):205–224, 1997. †BA126752 ga97aMorimoto. [1477] M. Sarkar and B. Yegnanarayana. Feedforward neural networks configuration using evolutionary programming. In Proceedings of the 1997 IEEE International Conference on Neural Networks, volume 1, pages 438–443, Houston, TX (USA), 9.-12. June 1997. IEEE, New York, NY. †CCA78929/97 ga97aMSarkar. [1478] Min Woong Hwang, Jin Young Choi, and Jaehong Park. Evolutionary projection neural networks. In Proceedings of 1997 IEEE International Conference on Evolutionary Computation, pages 667–671, Indianapolis, IN, 13.-16. April 1997. IEEE, New York, NY. †CCA44869/97 ga97aMWHwang. [1479] T. N. Nagabhushana and H. S. Chandrasekharaiah. Adaptive fault diagnosis of large interconnected power networks using genetic algorithms. Journal of the Indian Institute of Science, 77(1):95–106, JanuaryFebruary 1997. ga97aNagabhushana. [1480] N. Noguchi and H. Terao. Path planning of an agricultural mobile robot by neural network and genetic algorithm. Comput. Electron. Agric. (Netherlands), 18(2-3):187–204, 1997. †CCA80738/97 ga97aNoguchi. [1481] Norio Baba, T. Kita, Y. Takagawara, and K. Oda. Computer gaming systems utilizing neural networks and genetic algorithms. J. Soc. Instrum. Control Eng. (Japan), 36(6):434–448, 1997. In Japanese †CCA76130/97 ga97aNorioBaba. [1482] A. Obuchowicz and K. Politowicz. Evolutionary algorithms in optimisation of a multilayer feedforward neural network architecture. In Proceedings of the Fourth International Symposium on Methods and Models in Automation and Robotics, volume 2, pages 739–743, Miewdzyzdroje, Poland, 26.-29. August 1997. Wydawnictwo Uczelniane Politech. Szczecinskiej, Szczecin (Poland). †CCA9684/98 ga97aObuchowi. 142 Genetic algorithms and neural networks [1483] C. Ornes and Jack Sklansky. A neural network that explains as well as predicts financial market behavior. In Proceedings of the IEEE/IAFE 1997 Computational Intelligence for Financial Engineering, pages 43–49, New York, NY, 24.-24. March 1997. IEEE, New York, NY. †CCA76168/97 ga97aOrnes. [1484] Jo Ann Parikh, John S. DaPonte, Joseph N. Vitale, and George Tselioudis. Comparison of genetic algorithm systems with neural network and statistical techniques for analysis of cloud structures in midlatitude storm systems. Pattern Recognition Letters, 18(11-13):1347–13, November 1997. †toc ga97aParikh. [1485] P. Gomes, F. Pereira, and A. Silva. Empirical study of the influences of genetic parameters in the training of a neural network. In George D. Smith and Nigel C. Steele, editors, Proceedings of the International Conference on Artificial Neural Networks and Genetic Algorithms, pages 364–367, Norwich, UK, 2.-4. April 1997. Springer-Verlag, Berlin. ga97aPGomes. [1486] Andrei Popescu-Belis. An adaptive multi-agent system based on “neural darwinism”. In Proceedings of the First International Conference on Autonomous Agents, pages 484–485, Marina del Rey, CA (USA), 5.-8. February 1997. ACM Press. ga97aPopescu-Belis. [1487] D. Popovic and K. C. S. Murty. Retaining diversity of search point distribution through a breeder genetic algorithm for neural network learning. In Proceedings of the 1997 IEEE International Conference on Neural Networks, volume 1, pages 495–498, Houston, TX, 9.-12. June 1997. IEEE, New York, NY. †CCA78934/97 ga97aPopovic. [1488] Qiangfu Zhao. A co-evolutionary algorithm for neural network learning. In Proceedings of the 1997 IEEE International Conference on Neural Networks, volume 1, pages 432–437, Houston, TX, 9.-12. June 1997. IEEE, New York, NY. †CCA78928/97 ga97aQiangfuZhao. [1489] S. Rajasekaran and G. A. Vijayalakshmi Pai. Genetic algorithm based multilayer feedforward network as non linear regression correlator. In Ošmera [1933], pages 123–128. ga97aRajasekaran. [1490] R. E. Smith and H. Brown Cribbs III. Combined biological paradigms: a neural, genetics-based autonomous systems strategy. Robot. Auton. Syst. (Netherlands), 22(1):65–74, 1997. †CCA18202/98 ga97aRESmith. [1491] G. A. Riessen, G. J. Williams, and Xin Yao. PEPNet: parallel evolutionary programming for constructing artificial neural networks. In Proceedings of the 6th International Conference, Evolutionary Programming, pages 35–45, Indianapolis, IN, 13.-16. April 1997. Springer-Verlag, Berlin (Germany). †CCA74299/97 ga97aRiessen. [1492] R. M. Kil and Yoon-Seon Song. Optimization of a network with gaussian kernel functions based on genetic algorithm. In Proceedings of the 1997 International Conference on Neural Information Processing and Intelligent Information Systems, volume 1, pages 291–295, Dunedin (New Zealand), 24.-28. November 1997. Springer-Verlag, Singapore. †CCA74938/98 ga97aRMKil. [1493] Roman Neruda. Yet another genetic algorithm for feed-forward neural networks. In Proceedings of the Ninth IEEE International Conference on Tools with Artificial Intelligence, volume ?, pages 375–380, Newport Beach, CA, 3.-8. November 1997. IEEE Computer Society Press, Los Alamitos, CA. ga97aRNeruda. [1494] A. Rouvinen and H. Handroos. Robot positioning of a flexible hydraulic manipulator utilizing genetic algorithm and neural networks. In Proceedings of the Fourth Annual Conference on Mechatronics and Machine Vision in Practice, pages 182–187, Toowoomba (Australia), 23.-25. September 1997. IEEE, Piscataway, NJ. †P77390/97 ga97aRouvinen. [1495] Riccardo Poli. Discovery of symbolic, neuro-symbolic and neural networks with parallel distributed genetic programming. In George D. Smith and Nigel C. Steele, editors, Proceedings of the International Conference on Artificial Neural Networks and Genetic Algorithms, pages 419–423, Norwich, UK, 2.-4. April 1997. Springer-Verlag, Berlin. † ga97aRPoli. [1496] Robert Richardson. Neural networks compared to statistical techniques. In Proceedings of the 1997 IEEE/IAFE Conference on Computational Intelligence for Financial Engineering, pages 89–95, New York, NY, 23.-25. March 1997. IEEE, Piscataway, NJ. †EI M158518/97 ga97aRRichards. [1497] R. Salama and R. Owens. Evolving neural controllers for robot manipulators. In George D. Smith and Nigel C. Steele, editors, Proceedings of the International Conference on Artificial Neural Networks and Genetic Algorithms, pages 21–25, Norwich, UK, 2.-4. April 1997. Springer-Verlag, Berlin. ga97aRSalama. [1498] Sung-Bae Cho. Combining modular neural networks developed by evolutionary algorithm. In Proceedings of 1997 IEEE International Conference on Evolutionary Computation, pages 647–650, Indianapolis, IN, 13.-16. April 1997. IEEE, New York, NY. †CCA44867/97 ga97aS-BCho. [1499] Shyh-Jier Huang and Ching-Lien Huang. Application of genetic-based neural networks to thermal unit commitment. IEEE Transactions on Power Systems, 12(2):654–660, May 1997. (Proceedings of the IEEE/PES Summer Meeting, July 28 - August 1, 1996 Denver, CO) ga97aS-JHuang. Bibliography 143 [1500] Seung-Soo Han and Gary S. May. Using neural network process models to perform PECVD silicon dioxide recipe synthesis via genetic algorithms. IEEE Transactions on Semiconductor Manufacturing, 10(2):279– 287, May 1997. ga97aS-SHan. [1501] M. Sagrario Sánchez and Luis A. Sarabia. GINN (Genetic Inside Neural Network): Towards a nonparametric training. Analytica Chimica Acta, 348(1-3):533–542, 20. August 1997. (Proceedings of the International Conference on Chemometrics in Analytical Chemistry, Tarragona (Spain), June 25.-29. 1996) ga97aSagrarioSanchez. [1502] Sankar K. Pal, Susmita De, and Ashish Ghosh. Designing Hopfield type networks using genetic algorithms and its comparison with simulated annealing. International Journal of Pattern Recognition and Artificial Intelligence, 11(3):447–461, May 1997. ga97aSankarKPal. [1503] Roland Schwaiger and Helmut A. Mayer. Genetic algorithms to create training data sets for artificial neural networks. In Alander [1930], pages 153–162. (ftp://ftp.uwasa.fics/3NWGA/Schweiger.ps.Z) ga97aSchwaiger. [1504] Javier Segovia and Pedro Isasi. Genetic programming for designing ad hoc neural network learning rules. In Koza et al. [1929], page ? †conf.prog ga97aSegovia. [1505] Bernhard Sendhoff and Martin Kreutz. Evolutionary optimization of the structure of neural networks by a recursive mapping as encoding. In George D. Smith and Nigel C. Steele, editors, Proceedings of the International Conference on Artificial Neural Networks and Genetic Algorithms, pages 368–372, Norwich, UK, 2.-4. April 1997. Springer-Verlag, Berlin. † ga97aSendhoff. [1506] Seonha Ahn and Daijin Kim. Co-adaptation of SOMs by evolution and learning for an optimal VQ codebook design. J. KISS(B), Softw. Appl. (South Korea), 24(12):1319–1330, 1997. In Korean †CCA34430/98 ga97aSeonhAhn. [1507] S. Haring, Joost N. Kok, and M. C. Wezel. Feature selection for neural networks through functional links found by evolutionary computation. In X. Liu, P. Cohen, and M. Berthold, editors, Advances in Intelligent Data Analysis, Second International Symposium, IDA-97, volume LNCS of 1280, pages 199–210, London (UK), 4.-6. August 1997. Springer-Verlag Berlin Heidelberg. * www /Springer ga97aSHaring. [1508] Shengsong Mei, Zhuo Huang, and Kangling Fang. A neural network controller based on genetic algorithms. In Proceedings of the 1997 IEEE International Conference on Intelligent Processing Systems, volume 2, pages 1624–1628, Beijing (China), 28.-31. October 1997. IEEE, New York, NY. †CCA53686/98 ga97aShengMei. [1509] Sigeru Omatu and Michifumi Yoshioka. Self-tuning neuro-PID control and applications. In Proceedings of the 1997 IEEE International Conference on Systems, Man, and Cybernetics, volume 3, pages 1985–1989, Orlando, FL, 12.-15. October 1997. IEEE, Piscataway, NJ. †EI M029847/98 ga97aSigeruOmatu. [1510] S. Smolander and J. Lampinen. Determining the optimal structure for multilayer self-organizing map with genetic algorithm. In M. Frydrych, J. Parkkinen, and A. Visa, editors, Proceedings of the 10th Scandinavian Conference on Image Analysis (SCIA’97), volume 1, pages 411–418, Lappeenranta (Finland), 9.-11. June 1997. Pattern Recognition Society Finland. †P76623/97 ga97aSmolander. [1511] Sameh M. Yamany, K. J. Khiani, and Aly A. Farag. Application of neural networks and genetic algorithms in the classification of endothelian cells. Pattern Recognition Letters, 18(11-13):1205–1210, November 1997. †toc ga97aSMYamany. [1512] Toshio Fukuda, Youichirou Komata, and Takemasa Arakawa. Stabilization control of biped locomotion robot based learning with GAs having self-adaptive mutation and recurrent neural networks. In Proceedings of the 1997 IEEE International Conference on Robotics and Automation, volume 1, pages 217–222, Albuquerque, NM, 20.-25. April 1997. IEEE, New York, NY. †CCA81715/97 ga97aTFukuda. [1513] T. Kanno, H. Kumano, Y. Teramati, and H. Nagahashi. Designing neural networks for recognition of male and female faces using genetic algorithms. Transactions of the Institute of Electronics, Information, and Communication Engineers D-II (Japan), J80D-II(8):2251–2253, 1997. (In Japanese) †CCA93417/97 ga97aTKanno. [1514] Totu Kumagai, Mitsuo Wada, Sadayoshi Mikami, and Ryoichi Hashimoto. Structured learning in recurrent neural network using genetic algorithm with interval copy operator. In Proceedings of 1997 International Conference on Evolutionary Computation, pages 651–656, Indianapolis, IN, 13.-16. April 1997. IEEE, New York, NY. †CCA44868/97 ga97aTKumagai. [1515] T. Morimoto, J. Suzuki, and Y. Hashimoto. Optimization of a fuzzy controller for fruit storage using neural networks and genetic algorithms. Engineering Applications of Artificial Intelligence, 10(5):473–483, October 1997. ga97aTMorimoto. 144 Genetic algorithms and neural networks [1516] T. Olmez. Classifiation of ECG waveforms by using RCE neural networks and genetic algorithms. Electronics Letters, 33(18):1561–1562, 1997. †EI M010399/98 ga97aTOlmez. [1517] A. P. Topchy and O. A. Lebedko. Neural network training by means of cooperative evolutionary search. Nuclear Instruments & Methods in Physics Research A, 398(1-2):240–241, 1997. (Proceedings of the 5th International Workshop (AIHENP’96) on Software Engineering, Neural Nets, Genetic Algorithms, Expert Systems, Symbolic Algebra and Automatic Calculations in Physics Research UNIL-EPFL, Lausanne (Switzerland), 2.-6. Sep. 1996) ga97aTopchy. [1518] Ulrich Derigs and Gunnar Schirp. Genetic modeling of artificial neural nets: an application to credit evaluation. OR Spektrum (Germany), 19(4):285–293, 1997. In German †CCA690/98 ga97aUDerigs. [1519] Terry Van Belle. Is neural Darwinism Darwinism? Artificial Life, 3(1):41–49, ? 1997. * BA 140852/97 ga97aVanBelle. [1520] Z. J. Viharos and L. Monostori. Optimization of process chains by artificial neuronal networks and genetic algorithms using quality control charts. In B. Katalinic, editor, Proceedings of the 8th International DAAAM Symposium, pages 353–356, Dubrovnik, Croatia, 23.-25. October 1997. DAAAM International, Vienna, TU Wien. ga97aViharos. [1521] Francesco Vivarelli, Piero Fariselli, and Rita Casadio. The prediction of protein secondary structure with a cascade correlation learning architecture of neural networks. Neural Computat. Appl., 6(1):57–62, ? 1997. * CCA 98973/97 ga97aVivarelli. [1522] Eva Volná. Optimal selection of topology of neural network. In Ošmera [1933], pages 374–377. ga97aVolna. [1523] W. A. Farag, V. H. Quintana, and G. Lambert-Torres. Neuro-fuzzy modeling of complex systems using genetic algorithms. In Proceedings of the 1997 IEEE International Conference on Neural Networks, volume 1, pages 444–449, Houston, TX, 9.-12. June 1997. IEEE, New York, NY. †CCA78930/97 ga97aWAFarag. [1524] Wen Xu, Dazhong Wang, Zecun Zhou, and Heng Chen. Application of artificial neural network combined by genetic algorithm in fault diagnosis of power transformer. Zhongguo Dianji Gongcheng Xuebao, 17(2):109– 112, 1997. †EI M174039/97 ga97aWenXu. [1525] Slawomir Wesolkowski and Khaled Hassanein. Comparative study of combination schemes for an ensemble of digit recognition neural networks. In Proceedings of the 1997 IEEE International Conference on Systems, Man, and Cybernetics, volume 4, pages 3534–3539, Orlando, FL, 12.-15. October 1997. IEEE, Piscataway, NJ. †EI M024986/98 ga97aWesolkowski. [1526] T. Whitfort, B. Choi, C. Mathews, and J. McCullagh. An evolutionary approach to the specification of high performing backpropagation neural networks. In Proceedings of the 1997 International Conference on Neural Information Processing and Intelligent Information Systems, volume 1, pages 412–415, Dunedin (New Zealand), 24.-28. November 1997. Springer-Verlag, Berlin (Germany). †CCA70204/98 ga97aWhitfort. [1527] William S. Hortos. Comparison of neural network applications for channel assignment in cellular TDMA networks and dynamically sectored PCS networks. In Steven K. Rogers, editor, Application and Science of Artificial Neural Networks III, volume SPIE-3077, pages 508–524, ?, April 1997. The International Society for Optical Engineering. * www/SPIE Web ga97aWSHortos. [1528] Meng Xiang-Wu and Cheng Hu. Using evolutionary programming to construct Hopfield neural networks. In Proceedings of the 1997 IEEE International Conference on Intelligent Processing Systems, volume 1, pages 571–573, Beijing (China), 28.-31. October 1997. IEEE, New York. †CCA53685/98 ga97aXiang-Wu. [1529] XiaoXiao Tang and JieGu Li. Determination of the topology and weights of the feedforward ANN by genetic evolution. volume SPIE-3077, pages 367–371. Proc. SPIE - Int. Soc. Opt. Eng. (USA), 1997. †CCA53777/97 ga97aXiaoTang. [1530] Xiong Manli and Li Guangxi. The line loss calculation and forecasting of the electrical distribution network based on the neural network genetic algorithm. In Proceedings of the International Power Engineering Conference, volume 2, pages 856–860, Singapore, 22.-24. May 1997. Nanyang Technol. University, Singapore. †CCA56655/98 ga97aXiongManli. [1531] Xu Wen, Wang Dazhong, Zhou Zecun, and Chen Heng. Application of artificial neural network combined by genetic algorithm in fault diagnosis of power transformer. Proc. CSEE (China), 17(2):109–112, 1997. In Chinese †EEA70334/97 ga97aXWen. [1532] T. Yamada and H. Mizuno. Implementation of binary logic functions by 3-layer neural network models using genetic algorithms. Mem. Tokohu Inst. Technol. I, Sci. Eng. (Japan), (17):203–210, 1997. In Japanese †CCA56068/97 ga97aYamada. Bibliography 145 [1533] Yoshiji Fujimoto and Shigeyoshi Tsutsui. A peak shape identification genetic algorithm with a radial basis function. In Proceedings of 1997 IEEE International Conference on Evolutionary Computation, pages 349–354, Indianapolis, IN, 13.-16. April 1997. IEEE, New York, NY. †CCA 44464/97 ga97aYFujimoto. [1534] Yong-Hua Song, A. T. Johns, Q. Y. Xuan, and J. Y. Liu. Genetic algorithm based neural networks applied to fault clasification for EHV transmission lines with a UPFC. In Proceedings of the Sixth International Conference on Developments in Power System Protection, pages 278–281, Nottingham, UK, 25.-27. March 1997. IEE, London, UK. †EEA70018/97 ga97aYHSong. [1535] Yong Liu and Xin Yao. Evolving modular neural networks which generalise well. In Proceedings of the 1997 International Conference on Evolutionary Computation, pages 605–610, Indianapolis, IN, 13.-16. April 1997. IEEE, New York, NY. †CCA44862/97 ga97aYLiu. [1536] Y. M. Chen and R. M. OConnell. Active power line conditioner with a neural network control. IEEE Transactions on Industrial Applications, 33(4):1131–1136, 1997. †CCA72272/97 ga97aYMChen. [1537] Yuanhui Zhou, Yuchang Lu, and Chunyi Shi. Combining neural network, genetic algorithm and symbolic learning approach to discover knowledge from databases. In Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, pages 4388–4393, Orlando, FL, 12.-15. October 1997. IEEE, Piscataway, NJ. †A98-27042 ga97aYuanhuiZhou. [1538] Michele Zamparelli. Genetically trained cellular neural networks. Neural Networks, 10(6):1143–1151, August 1997. ga97aZamparelli. [1539] Z. Q. Bo, H. Y. Li, R. K. Aggarwal, A. T. Johns, and P. J. Moore. Noncommunication protection of transmission line based on genetic evolved neural network. In Proceedings of the Sixth International Conference on Developments in Power System Protection, pages 291–294, Nottingham, UK, 25.-27. March 1997. IEE, London, UK. †CCA59837/97 ga97aZQBo. [1540] A. D. Brown and H. C. Card. Evolutionary artificial neural networks. In Proceedings of the 1997 Canadian Conference on Electrical and Computer Engineering, volume 1, pages 313–317, St.John, Canada, 25.28. May 1997. IEEE, Piscataway, NJ. †EI M178994/97 ga97bADBrown. [1541] A. Imada and K. Araki. Random perturbations to Hebbian synapses of associative memory using a genetic algorithm. In Proceedings of the Biological and Artificial Computation: From Neuroscience to Technology, pages 398–407, Lanzarote, Spain, 4.-6. June 1997. Springer-Verlag, Berlin (Germany). †CCA78948/97 ga97bAImada. [1542] A. P. Topchy, O. A. Lebedko, V. V. Miagkikh, and N. K. Kasabov. Adaptive training of radial basis function networks based on cooperative evolution and evolutionary programming. In Proceedings of the 1997 International Conference on Neural Information Processing and Intelligent Information Systems, volume 1, pages 253–258, Dunedin (New Zealand), 24.-28. November 1997. Springer-Verlag, Singapore. †CCA74931/98 ga97bAPTopchy. [1543] A. R. Burton and T. Vladimirova. Genetic algorithm utilising neural network fitness evaluation for musical composition. In George D. Smith and Nigel C. Steele, editors, Proceedings of the International Conference on Artificial Neural Networks and Genetic Algorithms, pages 219–223, Norwich, UK, 2.-4. April 1997. ga97bARBurton. [1544] J. Balicki and Z. Kitowski. Genetic algorithms and neural networks for solving linear optimization problems. In Proceedings of the Fourth International Symposium on Medhods and Models in Automation and Robotics, volume 2, pages 705–710, Miewdzyzdroje, Poland, 26.-29. August 1997. Wadawnictwo Uczelniane Politech, Szczecin, Poland. †CCA9681/98 ga97bBalicki. [1545] Lee A. Belfore, II and Abdul-Rahman A. Arkadan. Neurogenetic models for the characterization of fault tolerant switched reluctance motors. In 1997 IEEE International Electric Machines and Drives Conference Record, pages TB1/8.1–TB1/8.3, Milwaukee, WI, 18.-21. May 1997. IEEE, New York. * CCA 68890/97 ga97bBelfore. [1546] Hugo De Garis, L. Kang, Qimhing He, Zhengjun Pan, M. Ootani, and E. Ronald. Million module neural systems evolution: the next step in ATR’s billion neuron artificial brain (“CAM-Brain”) project. In Proceedings of the Third European Conference on Artificial Evolution, Nimes (France), 22.-24. October 1997. Springer-Verlag, Berlin (Germany). †CCA34345/98 ga97bDeGaris. [1547] Dimitris C. Dracopoulos and Antonia J. Jones. Adaptive neuro-genetic control of chaos applied to the attitude control problem. Neural Comput. Appl. (UK), 6(2):102–115, 1997. †CCA11618/98 ga97bDracopoulos. [1548] Toshio Fukuda and Joji Shimojima. Hierarchical intelligent robotic system-adaptation, learning and evolution. In Blumenstein [1931], pages 1–5. ga97bFukuda. 146 Genetic algorithms and neural networks [1549] Garrison W. Greenwood. Training multiple layer perceptrons to recognize attractors. IEEE Transactions on Evolutionary Computation, 1(4):244–248, ? 1997. †Altavista/Greenwood ga97bGreenwood. [1550] Akira Imada and Keijiro Araki. Searching real-valued synaptic weights of Hopfields associative memory using evolutionary programming. In Proceedings of the 6th International Conference, pages 13–22, Indianapolis, IN, 13.-16. April 1997. Springer-Verlag, Berlin (Germany). †CCA74378/97 ga97bImada. [1551] Hisao Ishibuchi and Tomoharu Nakashima. Evolution of fuzzy nearest neightbor neural networks. In Proceedings of 1997 IEEE International Conerence on Evolutionary Computation, pages 673–678, Indianapolis, IN, 13.-16. April 1997. IEEE, New York, NY. †CCA44870/97 ga97bIshibuchi. [1552] D. Karaboga and A. Kalinli. Training recurrent neural networks for dynamic system identification using parallel tabu search algorithm. In Proceedings of the 1997 IEEE International Symposium on Intelligent Control, volume ?, pages 113–118, Istanbul (Turkey), 16.-18. July 1997. IEEE, Piscataway, NJ. †EI M008796/98 ga97bKaraboga. [1553] Halina Kwaśnicka. Evolutionary approach to artificial neural network design - good way or blind alley. In Ošmera [1933], pages 342–347. ga97bKwasnicka. [1554] Pedro Larra naga, Basilio Sierra, M. J. Gallego, M. J. Michelena, and J. M. Picaza. Learning Bayesian networks by genetic algorithms: a case study in the prediction of survival in malignant skin melanoma. In Proceedings of the 6th Conference on Artificial Intelligence in Medicine Europe, pages 261–272, Grenoble (France), 23.-26. March 1997. Springer-Verlag, Berlin (Germany). †CCA68337/97 ga97bLarranaga. [1555] Timothy Masters and Walker Land. A new training algorithm for the general regression neural network. In Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, volume 3, pages 1990–1994, Orlando, FL, 12.-15. October 1997. IEEE, Piscataway, NJ. †A98-23872 ga97bMasters. [1556] T. Morimoto, W. Purwanto, J. Suzuki, and Y. Hashimoto. Optimization of heat treatment for fruit during storage using neural networks and genetic algorithms. Comput. Electron. Agric. (Netherlands), 19(1):87–101, 1997. †CCA19870/98 ga97bMorimoto. [1557] M. Sarkar and B. Yegnanarayana. An evolutionary programming-based probabilistic neural networks construction technique. In Proceedings of the 1997 IEEE International Conference on Neural Networks, volume 1, pages 456–461, Houston, TX (USA), 9.-12. June 1997. IEEE, New York, NY. †CCA78931/97 ga97bMSarkar. [1558] K. Nagasaka, A. Konno, M. Inaba, and H. Inoue. Aquisition of visually guided swing motion based on genetic algorithms and neural networks in two-armed bipedal robot. In Proceedings of the 1997 IEEE International Conference on Robotics and Automation, volume 4, pages 2944–2949, Albuquerque, NM, 20.-25. April 1997. IEEE, New York, NY. †CCA81807/97 ga97bNagasaka. [1559] P. J. Jacob and A. D. Ball. Structuring a RBF classifier using genetic algorithm or a forward selection heuristic. In A. B. Bulsari and S. Kallio, editors, Proceedings of the 1997 International Conference on Engineering Applications of Neural Networks, pages 369–373, Stockholm (Sweden), 16.-18. June 1997. Systeemitekniikan seura ry, Turku (Finland). ga97bPJJacob. [1560] R. Neruda. Canonical genetic learning of RBF networks is faster. In George D. Smith and Nigel C. Steele, editors, Proceedings of the International Conference on Artificial Neural Networks and Genetic Algorithms, pages 350–353, Norwich, UK, 2.-4. April 1997. Springer-Verlag, Berlin. † ga97bRNeruda. [1561] Riccardo Poli. Parallel distributed genetic programming applied to the evolution of natural language recognisers. In Proceedings of the Evolutionary Computing, pages 163–177, Manchester, UK, 7.-8. April 1997. Springer-Verlag, Berlin (Germany). †CCA14901/98 ga97bRPoli. [1562] Ralf Salomon. Scaling behaviour of the evolution strategy when evolving neuronal control architectures for autonomous agents. In Proceedings of the 6th International Conference, Evolutionary Programming, pages 47–57, Indianapolis, IN, 13.-16. April 1997. Springer-Verlag, Berlin (Germany). †CCA72951/97 ga97bSalomon. [1563] Sigeru Omatu and Michifumi Yoshioka. Neuro-approach for intelligent systems development. In Proceedings of the 1997 IEEE International Conference on Neural Networks, volume 4, pages 2418–2423, Houston, TX, 9.-12. June 1997. IEEE, Piscataway, NJ. †EI M176594/97 ga97bSigeruOmatu. [1564] Takanori Shibata, Toshio Fukuda, and Kazuo Tanie. chapter 108. Synthesis of fuzzy, artificial intelligence, neural networks, and genetic algorithm for hierarchical intelligent control, pages 1364–1368. CRC Press, Boca Raton, FL, 1997. ga97bTakanoriShibata. [1565] Totu Kumagai, Mitsuo Wada, Sadayoshi Mikami, and Ryoichi Hashimoto. Dynamic control by recurrent neural networks through genetic algorithm. In A. B. Bulsari and S. Kallio, editors, Proceedings of the 1997 International Conference on Engineering Applications of Neural Networks, pages 333–336, Stockholm (Sweden), 16.-18. June 1997. Systeemitekniikan seura ry, Turku (Finland). ga97bTKumagai. Bibliography 147 [1566] B. H. V. Topping. Parallel mesh generation and the sub-domain generation method. In B. H. V. Topping, editor, Advances in Computational Mechanics with Parallel and Distributed Processing (Proceedings of the First Euro-Conference on Parallel and Distributed Computing for Computational Mechanics), page ?, Lochinver (Scotland), 26. April-1. May 1997. Saxe-Coburg Publications, Edinburgh. ga97bTopping. [1567] Lefteri H. Tsoukalas and Robert E. Uhrig. chapter 106. Hybrid artificial intelligence systems, pages 1346– 1359. CRC Press, Boca Raton, FL, 1997. ga97bTsoukalas. [1568] Wei Yan, Zhaoda Zhu, and Rong Hu. A hybrid genetic/BP algorithm and its application for radar target classification. In Proceedings of the IEEE 1997 National Aerospace and Electronics Conference, volume 2, pages 981–984, Dayton, OH, 14.-17. July 1997. IEEE, New York, NY. †CCA13276/98 ga97bWeiYan. [1569] Xin Yao and Yong Liu. A new evolutionary system for evolving artificial neural networks. IEEE Transactions on Neural Networks, 8(3):694–713, May 1997. ga97bYao. [1570] Zi-Jiang Yang, Setsuo Sagara, and Teruo Tsuji. System impulse response identification using a multiresolution neural network. Automatica, 33(7):1345–1350, 1997. †EI M176135/97 ga97bZi-JYang. [1571] Z. Q. Bo, H. Y. Li, R. K. Aggarwal, and A. T. Johns. Current transients based faulted phase selection technique using a genetic algorithm evolved neural network. In Proceedings of the 32nd Universities Power Engineering Conference, volume 2, pages 959–962, Manchester, UK, 10.-12. September 1997. UMIST, Manchester, UK. †CCA24657/98 ga97bZQBo. [1572] A. Imada and K. Araki. Evolution of random synaptic weights of the Hopfield associative memory: how chaotic trajectories turn into fixed point attractors? In Proceedings of the 1997 International Conference on Neural Information Processing and Intelligent Information Systems, volume 1, pages 452–455, Dunedin (New Zealand), 24.-28. November 1997. Springer-Verlag, Singapore (Singapore). †CCA66194/98 ga97cAImada. [1573] Dimitris C. Dracopoulos. Evolutionary Learning Algorithms for Neural Adaptive Control. Springer-Verlag, Berlin, 1997. †A. V. Fiacco/www ga97cDracopoulos. [1574] Mary Lou Padgett. chapter 104. Neural evolutionary and GA systems and applications, pages 1338–1345. CRC Press, Boca Raton, FL, 1997. ga97cPadgett. [1575] T. Furuhashi, S. Matsushita, H. Tsutsui, and Y. Uchikawa. Knowledge extraction from hierarchical fuzzy model obtained by fuzzy neural networks and genetic algorithm. In Proceedings of the 1997 IEEE International Conference on Neural Networks, volume 4, pages 2374–2379, Houston, TX, 9.-12. June 1997. IEEE, New York, NY. †CCA79192/97 ga97dFuruhashi. [1576] Garrison W. Greenwood. Training partially recurrent neural networks using evolutionary strategies. IEEE Transactions on Speech & Audio Processing, 5(2):192–194, ? 1997. †Altavista/Greenwood ga97dGreenwood. [1577] T. Furuhashi, S. Matsushita, and H. Tsutsui. Fuzzy modeling of nonlinear systems using fuzzy neural networks and genetic algorithm. In Proceedings of the 1997 International Conference on Neural Information Processing and Intelligent Information Systems, volume 2, pages 839–842, Dunedin (New Zealand), 24.28. ? 1997. Springer-Verlag, Singapore. †CCA66203/98 ga97dTFuruhashi. [1578] Toshio Fukuda, Youichirou Komata, and Takemasa Arakawa. Recurrent neural network with self-adaptive GAs for biped locomotion robot. In Proceedings of the 1997 IEEE international Confeence on Neural Networks, volume 3, pages 1710–1715, Houston, TX, 9.-12. June 1997. IEEE, Piscataway, NJ. †EI M178899/97 ga97dToFukuda. [1579] Toshiyuki Ogawa. Neural network, 1997. fi.espacenet.com ga97dToshiyukiOgawa. (JP patent no. 9006881. Issued January 10 1997) * [1580] S.-H. Chen and Chih-Chi Ni. Evolutionary artificial neural networks and genetic programming: a comparative study based on financial data. In George D. Smith and Nigel C. Steele, editors, Proceedings of the International Conference on Artificial Neural Networks and Genetic Algorithms, pages 397–400, Norwich, UK, 2.-4. April 1997. ga97eS-HChen. [1581] Hisao Ishibuchi, Manabu Nii, and Tadahiko Murata. Linguistic rule extraction from neural networks and genetic-algorithm-based rule selection. In Proceedings of the 1997 IEEE International Conference on Neural Networks, volume 4, pages 2390–2395, Houston, TX, 9.-12. June 1997. IEEE, Piscataway, NJ. †EI M176936/97 ga97fIshibuchi. [1582] J. Aguilar and A. Colmenares. Resolution of pattern recognition problems using a hybrid genetic/random neural network learning algorithm. Pattern Anal. Appl. (UK), 1(1):52–61, 1998. †CCA53592/99 ga98aAguilar. 148 Genetic algorithms and neural networks [1583] A. I. Taalab, H. A. Darwish, and T. A. Kawady. ANN-based novel fault detector for generator windings protection. IEEE Transactions on Power Delivery, 14(3):824–830, July 1998. * www/IEEE ga98aAITaalab. [1584] A. K. Srivastava, K. K. Shukla, and S. K. Srivastava. Exploring neuro-genetic processing of electronic nose data. Microelectronics Journal, 29(11):921–931, 1998. ga98aAKSrivastava. [1585] Alan D. Blair, Elizabeth Sklar, and Pablo Funes. Co-evolution, determinism and robustness. In Bob McKay, Xin Yao, Charles S. Newton, Jong-Hwan Kim, and Takeshi Furuhashi, editors, Simulated Evolution and Learning (SEAL-98), volume 1585 of Lecture Notes in Artificial Intelligence, page ?, ?, ? 1998. SpringerVerlag, Berlin. ga98aAlanDBlair. [1586] M. Alderighi, S. De’Angelo, G. R. Sechi, and F. de’Ovidio. Experimenting genetic algorithms for training a neural network prototype for photon event identification. In Proceedings of the Thirty-First Hawaii International Conference on System Sciences, volume 3, pages 283–291, Kohala Coast, HI (USA), 6.9. January 1998. IEEE Computer Society Press, Los Alamitos , CA. †CCA32146/98 ga98aAlderighi. [1587] Anja Maria Reimetz. Strukturbestimmung von probablistischen neuronalen Netzen mit Hilfe von Evolutionären Algorithmen, 1998. ? †Wiegand ga98aAMReimetz. [1588] T. Andersen and T. Martinez. Constructing high order perceptrons with genetic algorithms. In Proceedings of the 1998 IEEE International Joint conference on Neural Networks, volume 3, pages 1920–1925, Provo, UT (USA), 4.-9. May 1998. IEEE, New York, NY. †CCA84491/98 ga98aAndersen. [1589] A. Ngom, I. Stojmenovic, and Z. Obradovic. Minimization of multivalued multithreshold perceptrons using genetic algorithms. In Proceedings of the International Symp on Multiple-Valued Logic, pages 209– 214, Fukuoka, Japan, 27.-29. May 1998. IEEE Computer Society Press, Los Alamitos , CA. †P80600 ga98aANgom. [1590] A. Radi and Riccardo Poli. Discovery of backpropagation learning rules using genetic programming. In Proceedings of the IEEE World Congress on Computational Intelligence, pages 371–375, Anchorage, AK (USA), 4.-9. May 1998. IEEE, New York, NY. †CCA75023/98 ga98aARadi. [1591] A. R. Bohari and N. Mizuno. Training and structure design of feedforward neural networks by employing genetic algorithms. In Proceedings of the 1998 Japan-U.S.A. Symposium on Flexible Automation, pages 769–776, Otsu, Japan, 12.-15. July 1998. Institute Systems, Control & Information Engineers. †P83752 ga98aARBohari. [1592] Anthony Richard Burton. A hybrid neuro-genetic pattern evolution system applied to musical composition. PhD thesis, University of Surrey, School of Electronic Engineering, 1998. (http://www.ee.surrey.ac.uk/ Personal/A.Burton/work.html) ga98aARBurton. [1593] Aaron R. Dinner, Sung-Sau So, and Martin Karplus. Use of quantitative structure-property relationships to predict the folding ability of model proteins. Proteins: Structure, Function, and Genetics, 33(2):177–203, 1. November 1998. ga98aARDinner. [1594] Ari S. Nissinen and Heikki Hyötyniemi. Evolutionary self-organizing map. In ?, editor, Proceedings of the 6th European Congress on Intelligent Techniques & Soft Computing, volume ?, pages 1596–1600, Aachen (Germany), 7.-10. September 1998. ERUDIT, Germany. ga98aAriNissinen. [1595] J. Balicki, K. Ficon, and Z. Kitowski. Evolutionary algorithms cooperated with the family of artificial neural networks for solving multiobjective optimization problems. In Proceedings of the Fifth International Symposium on Methods and Models in Automation and Robotics, volume 2, pages 621–626, Miedzyzdroje (Poland), 25.-29. August 1998. Tech. Univ. Szczecin, Szczecin (Poland). †CCA58682/99 ga98aBalicki. [1596] R. Baumgart-Schmitt, W. M. Herrmann, and R. Eilers. On the use of neural network techniques to analyse sleep EEG data. third communication: robustification of the classificator by applying an algorithm obtained from 9 different networks. Neuropsychobiology, 37(?):49–58, ? 1998. †[1840] ga98aBaumgart-Schmitt. [1597] T. Březina and Jiřı́ Krejsa. A few notes about neural nets generated via cellular grammar. In Ošmera [1934], pages 240–244. ga98aBrezina. [1598] Brian S. Allen, E. D. Jansing, John E. Selvage, and Darrel L. Chenoweth. Neural and genetic approximations of fractal error. In Proceedings of the 1998 IEEE Aerospace Conference, volume 4, pages 205–220, Aspen, CO, 21.-28. March 1998. IEEE, Piscataway, NJ. †A98-34543 ga98aBriAllen. [1599] Bernhard Sendhoff. Evolution of structures - Optimization of artificial neural structures for information processing. PhD thesis, Ruhr-University of Bochum, Institute for Neuroinformatics, 1998. ? †Wiegand ga98aBSendhoff. [1600] Chin-Teng Lin, Chong-Ping Jou, and Cheng-Jiang Lin. GA-based reinforcement learning for neural networks. Int. J. Syst. Sci. (UK), 29(3):233–247, 1998. †CCA34276/98 ga98aChin-TengLin. Bibliography 149 [1601] Ching Ching Shih, Kewei Zuo, and Wen-Teng Wu. Optimal fed-batch culture for penicillin G production via a hybrid neuralmodel and a real coded genetic algorithm. In Toshiomi Yoshida and Suteaki Shioya, editors, Computer Applications in Biotechnology (Proceedings of the 7th International Conference) CAB7, pages 51–54, Osaka (Japan), May 31.- June 4. 1998. IFAC Publications, Elsevier Science Ltd., Oxford (UK). †TKK/AS/Halme ga98aChingChingShih. [1602] C. H. Kung, C. M. Huang, C. M. Kung, and M. J. Devaney. An adaptive power-system load forecasting scheme using a genetic algorithm embedded neural-network. In Proceedings of the IEEE Instrumentation & Measurement Technology Conference, volume 1, pages 308–311, St. Paul, MN (USA), 18.-21. May 1998. IEEE, New York, NY. †P80877 ga98aCHKung. [1603] Chulkyu Shin, Sangmin Lee, Eunsil Lee, Jangwoo Kwon, Younggun Jang, and Seunghong Hong. A study on electromyogram signal technique using neural network and genetic algorithms. J. Inst. Electron. Eng. Korea S (South Korea), 35-S(11):176–183, 1998. In Korean †PA62795/99 ga98aChulShin. [1604] M. Clergue and Philippe Collard. Genetic algorithm for artificial neurogenesis. In Proceedings of the 1998 IEEE International Conference on Evolutionary Computation, pages 410–415, Anchorage, AK (USA), 4.-9. May 1998. IEEE, New York, NY. †CCA75026/98 ga98aClergue. [1605] E. DeRouin, J. R. Brown, and G. Denney. Feature-selection for neural-network classifiers using saliency and genetic algorithms. In Proceedings of the Applications and Sciece of Computational Intelligence, pages 322–331, Orlando, FL, 13.-16. April 1998. SPIE – International Society for Optical Engineering. †P80079 ga98aDeRouin. [1606] Devil H. Yip and William W. Yu. Novel design of neural networks for handwritten Chinese character recognition. In Robert A. Melter, Angela Y. Wu, and Login J. Latecki, editors, Vision Geometry VII, volume SPIE-3454, pages 324–329, ?, October 1998. The International Society for Optical Engineering. * www/SPIE Web ga98aDHYip. [1607] Dong-Wook Lee and Kwee-Bo Sim. Ontogenesis of artificial neural networks based on L-system and genetic algorithms. In Proceedings of the 5th International Conference on Soft Computing and Information/Intelligent Systems, volume 2, pages 817–820, Fukuoka, Japan, 16.-20. October 1998. World Scientific, Singapore. †CCA68420/99 ga98aDong-Lee. [1608] Du-Yih Tsai. Classification of heart diseases in ultrasonic images using neural networks trained by genetic algorithms. In Proceedings of the 1998 Fourth International Conference on Signal Processing, volume 2, pages 1213–1216, Beijing (China), 12.-16. October 1998. IEEE, Piscataway, NJ. †CCA84921/99 ga98aDu-YTsai. [1609] Dusko Katic and Miomir Vukobratovic. A neural network-based classification of environment dynamics for compliant of manipulation robots. IEEE Transactions on Systems, Man, and Cybernetics, 28(1):58–69, 1998. †A98-18041 ga98aDuskoKatic. [1610] Edward E. Derouin, Joe R. Brown, and Guy Denney. Feature selection for neural network classifier using saliency and genetic algorithms. In Steven K. Rogers, David B. Fogel, James C. Bezdek, and Bruno Bosacchi, editors, Applications and Science of Computational Intelligence, volume SPIE-3390, pages 322–331, ?, March 1998. The International Society for Optical Engineering. * www/SPIE Web ga98aEEDerouin. [1611] E. F. Mendes and A. C. P. Decarvalho. Target recognition using evolutionary neural networks. In Proceedings of the 5th Brazilian Symposium on Neural Networks, pages 226–231, Belo Horizont, Brazil, 9.-11. December 1998. IEEE Computer Society Press, Los Alamitos , CA. †P83276 ga98aEFMendes. [1612] E. T. H. Heng, D. Srinivasan, and A. C. Liew. Short term load forecasting using genetic algorithm and neural networks. In Proceedings of the 1998 International Conference on Energy Management and Power Delivery, volume 2, pages 576–581, Singapore, 3.-5. March 1998. IEEE, New York, NY. †CCA64569/98 ga98aETHHeng. [1613] Eva Volná. The problem of network design. In Ošmera [1934], pages 300–304. ga98aEVolna. [1614] F. Pasemann. Evolving neurocontrollers for balancing an inverted pendulum. Network: Comput. Neural Syst., 9(?):495–511, ? 1998. * www ga98aFPasemann. [1615] G. Betta, C. Liguori, and A. Pietrosantro. An advanced neural-network-based instrument fault detection and isolation scheme. IEEE Transactions on Instrumentation and Measurement, 47(2):507–512, April 1998. * www/IEEE ga98aGBetta. [1616] G. P. J. Schmitz and Chris Aldrich. Neurofuzzy modeling of chemical process systems with ellipsoidal radial basis function neural networks and genetic algorithms. Computers in Chemical Engineering, 22:S1001– S1004, 1998. †CCA50101/98 ga98aGPJSchmitz. 150 Genetic algorithms and neural networks [1617] M. Grzenda and B. Macukow. Genetic algorithm and neural networks to solve the prisoner’s dilemma. Opt. Mem. Neural Netw. (USA), 7(3):171–176, 1998. †PA83372/99 ga98aGrzenda. [1618] Heung Bum Kim, Sung Hoon Jung, and Kyu Ho Park. Adaptive learning-rate selection for BPNN using evolutionary programming. J. Electr. Eng. Inf. Sci. (Taiwan), 3(5):551–562, 1998. †CCA72582/99 ga98aHeungKim. [1619] Hyo-Byung Jun, Dae-Joon Kim, and Kwee-Bo Sim. Structure optimization of neural network using coevolution. J. Inst. Electron. Eng. Korea S (South Korea), 35-S(4):67–75, 1998. In Korean †CCA86060/98 ga98aHyo-BJun. [1620] Takumi Ichimura and Y. Kuriyama. Learning of neural networks with parallel hybrid GA using a royal road function. In Proceedings of the 1998 IEEE International Joint Conference on Neural Networks, volume 2, pages 1131–1136, Anchorage, AK (USA), 4.-9. May 1998. IEEE, New York, NY. †cca84442/98 ga98aIchimura. [1621] I. Ciuca and E. Jitaru. On the recurrent neural network induction by evolutionary computtions with applications in forecasting. Stud. Inf. Control (Romania), 7(2):187–191, 1998. †CCA75048/98 ga98aICiuca. [1622] Joao A. Arantes Do Amaral, Pedro L. Botelho, Nelson F. Ebecken, A. E. Xavier, and L. P. Caloba. Ship’s classification by its magnetic signature: a neurogenetic approach. In Firooz A. Sadjadi, editor, Automatic Target Recognition VIII, volume SPIE-3371, pages 314–321, ?, September 1998. The International Society for Optical Engineering. * www/SPIE Web ga98aJAArantesDoAmaral. [1623] A. Janczak. Evolutionary learning algorithm for recurrent multilayer perceptron. In Proceedings of the Fifth International Symposium on Methods and Models in Automation and Robotics, volume 2, pages 627– 632, Miedzyzdroje (Poland), 25.-29. August 1998. Tech. Univ. Szczecin (Szczecin, Poland). †CCA53500/99 ga98aJanczak. [1624] J. C. Figueira Pujol and Riccardo Poli. Evolving neural networks using a dual representation with a combined crossover operator. In Proceedings of the 1998 IEEE International Conference on Evolutionary Computation, pages 416–421, Anchorage, AK (USA), 4.-9. May 1998. IEEE, New York, NY. †CCA75027/98 ga98aJCFPujol. [1625] J. Da Silva Dias, J. M. Barreto, S. Nassar, and L. M. Brasil. Genetic and back-propagation algorithm in hybrid training of artificial neural networks: a unimodal search procedure. In Proceedings of the 16th IASTED International Conference, pages 37–40, Garmisch-Partenkirchen, Germany, 23.-25. February 1998. IASTED/ACTA Press, Anaheim, CA (USA). †CCA86510/99 ga98aJDaSDias. [1626] M. F. Jefferson, N. Pendleton, S. Mohamed, E. Kirkman, R. A. Little, S. B. Lucas, and M. A. Horan. Prediction of hemorrhagic blood loss with a genetic algorithm neural network. Journal of Applied Physiology, 84(1):357–361, 1998. †BA87806 ga98aJefferson. [1627] Jinn-Moon Yang, Jorng-Tzong Horng, and Cheng-Yan Kao. A new evolutionary approach to developing neural autonomous agents. In Sproceedings of the 1998 IEEE International Conference on Robotics and Automation, volume 2, pages 1411–1416, Leuven (Belgium), 16.-20. May 1998. IEEE, New York, NY. †CCA60120/98 ga98aJinn-MoonYang. [1628] Jérôme Kodjabachian and Jean-Arcady Meyer. Evolution and development of neural controllers for locomotion, gradient-following, and obstacle-avoidance in artificial insects. IEEE Transactions on Neural Networks, 9(5):796–812, September 1998. ga98aJKodjabachian. [1629] J. Murata, N. Nakamura, K. Hirasawa, K. Tanaka, and M. Sasaki. Neural network structure design using genetic algorithms. Trans. Inst. Electr. Eng. Jpn. C (Japan), 118-C(7-8):1114–1121, 1998. In Japanese †CCA84299/98 ga98aJMurata. [1630] J. V. Hansen. Comparative performance of backpropagation networks designed by genetic algorithms and heuristics. Int. J. Intell. Syst. Account. Financ. Manage. (UK), 7(2):69–79, 1998. †CCA79370/98 ga98aJVHansen. [1631] J. W. Wang, J. S. Pan, C. H. Chen, and H. L. Fang. Wavelet-based signal approximation with multilevel learning algorithms using genetic neuron selection. In Proceedings of the Tenth IEEE International Conference on Tools With Artificial Intelligence, pages 344–353, Taipei, Taiwan, 10.-12. November 1998. IEEE Computer Society Press, Los Alamitos , CA. †P84302 ga98aJWWang. [1632] Youli Andreev Kanev. Application of neural networks and genetic algorithms in high energy physics. PhD thesis, University of Florida, 1998. (UMI No.DA9905968) †ChA 357937y/99 ga98aKanev. [1633] N. K. Kasabov. Evolving fuzzy neural networks: theory and applications for on-line adaptive prediction, decision making and control. Aust. J. Intell. Inf. Process. Syst. (Australia), 5(3):154–160, 1998. †CCA54371/99 ga98aKasabov. Bibliography 151 [1634] J. Keppler. Optimal operation of gas and steam-turbine power-plants with genetic algorithms and neural networks. In Proceedings of the Computational Intelligence: Industrial Application of Neural Networks, Evolutionary Algorithms and Fuzzy Control, pages 87–100, Berlin (Germany), 3.-4. March 1998. VDIVerlag. †P80878 ga98aKeppler. [1635] G. Kleymenov, A. Piskounov, and S. Vdovichev. Genetic learning of neural networks in approximation of multivariable functions. In Proceedings of the 6th European Congress on Intelligent Techniques and Soft Computing, volume 2, pages 1277–1280, Aachen (Germany), 7.-10. September 1998. Verlag Mainz, Aachen (Germany). †CCA68527/99 ga98aKleymeno. [1636] Jérôme Kodjabachian and Jean-Arcady Meyer. Evolution and development of neural controllers for locomotion, gradient-following, and obstacle-avoidance in artificial insects. IEEE Trans. Neural Netw. (USA), 9(5):796–812, 1998. †CCA77848/98 ga98aKodjabac. [1637] K. Satomi, M. Fujimoto, Minoru Fukumi, and N. Akamatsu. Rule extraction from small-sized neural networks formed using a genetic algorithm. In Proceedings of the 5th International Conference on Soft Computing and Information/Intelligent systems, volume 2, pages 644–647, Fukuoka, Japan, 16.-20. October 1998. World Scientific, Singapore. †CCA72581/99 ga98aKSatomi. [1638] Kazuo Shirakawa, Masahiko Shimizu, Naofumi Okubo, and Yosimasa Daido. Structural determination of multilayered large-signal neural-network HEMT model. IEEE Transactions on Microwave Theory and Techniques, 46(10):1367–1375, October 1998. ga98aKShirakawa. [1639] T. Kumagai, M. Wada, S. Mikami, and R. Hashimoto. Learning of recurrent neural networks through genetic algorithm with internal copy operator. Transactions of the Institute of Electronics, Information, and Communication Engineers D-II, J81D-II(2):378–385, 1998. (In Japanese) †CCA34302/98 ga98aKumagai. [1640] Kyoung-Jae Won, Jae-Yong Seo, Jung-Heum Yon, Seong-Hyun Kim, and Hong-Tae Jeon. On designing an intelligent control system using immunized neural network. J. Inst. Electron. Eng. Korea S (South Korea), 35-S(12):27–35, 1998. In Korean †CCA54534/99 ga98aKyounWon. [1641] Lars Nolle, Alun Armstrong, and Andrew Ware. Optimisation of work roll profiles in a 2-high rolling mill stand by means of computational intelligence. In Ošmera [1934], pages 277–284. ga98aLarNolle. [1642] Lakhmi C. Jain and N. M. Martin. Fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms: Industrial Applications. CRC Press, Boca Raton, FL, 1998. †www /CRC Press ga98aLCJain. [1643] Li-Der Chou and J.-L. C. Wu. Bandwidth allocation of virtual paths using neural-network-based genetic algorithms. IEE Proc. Commun. (UK), 145(1):33–39, 1998. †CCA41543/98 ga98aLi-DChou. [1644] Loi Lei Lai. Intelligent System Applications in power Engineering, Evolutionary Programming and Neural Networks. John Wiley & Sons, Chichester, 1998. ga98aLLLai. [1645] L. M. Brasil, F. M. Deazevedo, J. M. Barreto, and M. Noirhommefraiture. A neuro-fuzzy-ga system architecture for helping the knowledge acquisition process. In Proceedings of the IEEE International Joint Symposia on Intelligence and Systems, pages 57–64, Rockville, MD (USA), 21.-23. May 1998. IEEE Computer Society Press, Los Alamitos , CA. †CCA63291/98 P80657 ga98aLMBrasil. [1646] Lemuel R. Myers, John G. Keller, Steven K. Rogers, and Matthew Kabrisky. Evolution programs for Bayesian training of neural networks. In Steven K. Rogers, David B. Fogel, James C. Bezdek, and Bruno Bosacchi, editors, Applications and Science of Computational Intelligence, volume SPIE-3390, pages 90–98, ?, March 1998. The International Society for Optical Engineering. * www/SPIE Web ga98aLRMyers. [1647] Mu-Chun Su and Hsiao-Te Chang. Genetic-algorithms-based approach to self-organizing feature map and application in cluster analysis. In The 1998 IEEE International Joint Conference on Neural Networks Proceedings. IEEE World Congress on Computational Intelligence, volume 1, pages 735–740, Anchorage, AK, USA, 4.-9.May 1998. IEEE, Piscataway, NJ. * www/IEEE ga98aM-CSu. [1648] Marko A. Grönroos. Evolutionary design of neural networks. Master’s thesis, University of Turku, Department of Mathematical Sciences, 1998. (http://www.utu.fi/∼magi/opinnot/gradu/) ga98aMAGronroos. [1649] Masanori Takuma, Noboru Shinke, and Mitsukazu Ochi. Study on support system for design of composite laminated plate (1st report, application of genetic algorithm and neutral network). Nippon Kikai Gakkai Ronbunshu, A-hen, 64(624):2080–2086, 1998. †ChA25900j/99 ga98aMasanoriTakuma. [1650] M. Borairi and H. Wang. Actuator and sensor fault diagnosis of nonlinear dynamic systems via genetic neural networks and adaptive parameter estimation technique. In Proceedings of the 1998 IEEE International Conference on Control Applications, volume 1, pages 278–282, Trieste, Italy, 1.-4.September 1998. IEEE, Piscataway, NJ. * www/IEEE ga98aMBorairi. 152 Genetic algorithms and neural networks [1651] Minoru Fukumi and N. Akamatsu. A genetic algorithm with deterministic mutation based on neural network learning. Syst. Comput. Jpn. (USA), 29(3):10–17, 1998. †CCA58338/98 ga98aMFukumi. [1652] M. Hanggi and G. S. Moschytz. Genetic optimization of cellular neural networks. In Proceedings of the 1998 IEEE International Conference on Evolutionary Computation, pages 381–386, Anchorage, AK (USA), 4.-9. May 1998. IEEE, New York, NY. †CCA75024/98 ga98aMHanggi. [1653] M. H. Wong, Y. K. Wong, and T. S. Chung. Parameter determination of an evolving neural network approach in unit commitment solution. In IEEE International Conference on Systems, Man, and Cybernetics, volume 2, pages 1631–1636, San Diego, CA, 11.-14. October 1998. IEEE, Piscataway, NJ. ga98aMHWong. [1654] Masashi Kamo, Takuya Kubo, and Yoh Iwasa. Neural network for female mate preference, trained by a genetic algorithm. Philosophical Transactions of the Royal Society of London B Biological Sciences, 353(1367):399–406, 29. March 1998. * ISI BA 167509/98 ga98aMKamo. [1655] Michael Korkin, Norberto Eiji Nawa, and Hugo de Garis. A ”spike interval information coding” representation for ATR’s CAM-brain machine (CBM). In M. Sipper, D. Mange, and A. Pérez-Uribe, editors, Evolvable Systems: From Biology to Hardware, Second International Conference, ICES 98, volume LNCS of 1478, pages 256–268, Lausanne (Switzerland), September 1998. Springer-Verlag Berlin Heidelberg. * www /Springer ga98aMKorkin. [1656] Mary Lou Padgett, Thaddeus A. Robbel, and John L. Johnson. Pulse-coupled neural networks PCNN and new approaches to biosensor applications. In Steven K. Rogers, David B. Fogel, James C. Bezdek, and Bruno Bosacchi, editors, Applications and Science of Computational Intelligence, volume SPIE-3390, pages 79–88, ?, March 1998. The International Society for Optical Engineering. * www/SPIE Web ga98aMLPadgett. [1657] Jahangir Morshed and Jagath J. Kaluarachchi. Parameter estimation using artificial neural network and genetic algorithm for free - product migration and recovery. Water Resour. Res., 34(5):1101–1113, 1998. †ChA128:326026e ga98aMorshed. [1658] Marco Russo. FuGeNeSys-a fuzzy genetic neural system for fuzzy modeling. IEEE Transactions on Fuzzy Systems, 6(3):373–388, 1998. †[1935] CCA74732/98 ga98aMRusso. [1659] M. J. Watts and N. K. Kasabov. Genetic algorithms for the design of fuzzy neural networks. In Proceedings of the Fifth International Conference on Neural Information Processing Jointly with JNNS’98: The 1998 Annual Conference of the Japanese Neural Networks Society, pages 793–796, Kitakyushu, Japan, 21.23. October 1998. IOS Press, Amsterdam. †P793 ga98aMWatts. [1660] Nobuo Funabiki, Junji Kitamichi, and Seishi Nishikawa. An evolutionary neural network approach for module orientation problems. IEEE Transactions on Systems, Man, and Cybernetics, 28(6):849–855, December 1998. ga98aNFubabiki. [1661] N. M. Ershov. Neural network architecture optimization by genetic algorithms. Mosc. Univ. Comput. Math. Cybern. (USA), (4):30–32, 1998. †CCA82145/99 ga98aNMErshov. [1662] N. Silva, H. Macedo, and A. Rosa. Evolutionary fuzzy neural networks automatic design of rule based controllers of nonlinear delayed systems. In Proceedings of the 1998 IEEE International Conference on Fuzzy Systems, volume 2, pages 1271–1276, Anchorage, AK (USA), 4.-9. May 1998. IEEE, New York, NY. †CCA85944/98 ga98aNSilva. [1663] P. Angelov, R. Guthke, and R. Berkholz. Optimal control of a fermatation process using neural networks and genetic algorithms. In ?, editor, Proceedings of the 6th European Congress on Intelligent Techniques and Soft Computing (EUFIT’98), volume 3, pages 1591–1595, Aachen (Germany), 7.-10. September 1998. Verlag Mainz, Aachen. * CCA 79373/99 ga98aPAngelov. [1664] Manolis Papadrakakis, Nikos D. Lagaros, and Yiannis Tsompanakis. Structural optimization using evolution strategies and neural networks. Computer Methods in Applied Mechanics and Engineering, 156(14):309–333, 1998. ga98aPapadrak. [1665] Philippe Biela Enberg, Denis Hamad, and Jack Gerard Postaire. Unsupervised data classification with neural elastic networks and genetic algorithms. In Ošmera [1934], pages 249–254. ga98aPBEnberg. [1666] V. Petridis, E. Paterakis, and A. Kehagias. A hybrid neural-genetic multimodel parameter estimation algorithm. IEEE Transactions on Neural Networks, 9(5):862–876, 1998. †CCA74806/98 ga98aPetridis. [1667] P. Hajda, V. Novotny, X. Feng, and R. L. Yang. Simple feedback logic, genetics algorithms and artificial neural networks for real-time control of a collection system. Water Science and Technology, 38(3):187–196, 1998. †P82848 ga98aPHajda. Bibliography 153 [1668] Prabhat Hajela and B. Kim. Classifier systems for enhancing neural network-based global function approximations. In Proceedings of the 7th AIAA/USAF/NASA/ISSMO Symposium on Multisciplinary Analysis and Optimization, pages 371–380, St. Louis, MO, 2.-4. September 1998. American Institute of Aeronautics and Astronautics, Reston, VA. †A98-39739 ga98aPHajela. [1669] Qingyue Pan, Renguo Song, Qizhi Zhang, Weidong Huang, and Yaohe Zhou. Optimization of laser surface melting technology for 1Cr18Ni9Ti stainless steel based on artificial neural networks/genetic algorithm. Cailiao Yanjiu Xuebao, 12(3):251–256, 1998. †ChA345711m/98 ga98aQingyPan. [1670] Q. Y. Pan, W. D. Huang, R. G. Song, Y. H. Zhou, and G. L. Zhang. The improvement of localized corrosion resistance in sensitized stainless steel by laser surface remelting. Surface and Coatings Technology, 102(?):245–255, ? 1998. ga98aQYPan. [1671] N. Richards, D. E. Moriarty, and R. Miikkulainen. Evolving neural networks to play Go. Appl. Intell., Int. J. Artif. Intell. Neural Netw. Complex Probl.-Solving Technol. (Netherlands), 8(1):85–96, 1998. †CCA43111/98 ga98aRichards. [1672] R. S. Sexton, R. E. Dorsey, and J. D. Johnson. Toward global optimization of neural networks: a comparison of the genetic algorithm and backpropagation. Decis Support Syst. (Netherlands), 22(2):171–185, 1998. †CCA58209/98 ga98aRSSexton. [1673] D. Rutkowska. On generating fuzzy rules by an evolutionary approach. Cybernetics and Systems, 29(4):391– 407, June 1998. †CCA80953/98 ga98aRutkowska. [1674] Sang-Woon Kim, Seong-Hyo Shin, and Y. Aoki. A structural learning of neural-network classifiers using PCA networks and species genetic algorithms. IEICE Transactions on Fundamentals of Electronics, Communications and Computer Science, E81-A(6):1183–1186, 1998. †CCA66290/98 ga98aSang-Kim. [1675] Sung Bae Cho and Katsunori Shimohara. Evolutionary learning of modular neural networks with genetic programming. Applied Intelligence, 9(3):191–200, November-December 1998. * PsycINFO2000-03679-001 ga98aSBCho. [1676] S. C. Shin and S. B. Park. GA-based predictive control for nonlinear processes. IEEE Electronics Letters, 34(20):1980–1981, ? 1998. †[1936] ga98aSCShin. [1677] J. Segovia and P. Isasi. Genetic programming for learning rule search in neural nets. Neural Netw. World ( Czech Republic), 8(2):201–212, 1998. †CCA58207/98 ga98aSegovia. [1678] R. Seliger, B. Koppenseliger, and P. M. Frank. Neurogenetic prognosis of financial data. In Proceedings of the Computational Intelligence: Industrial Application of Neural Networks, Evolutionary Algorithms and Fuzzy Control, pages 335–346, Berlin (Germany), 3.-4. March 1998. VDI-Verlag. †P80878 ga98aSeliger. [1679] S. A. Sergeev, K. V. Mahotilo, G. K. Voronovsky, and S. N. Petrashev. Genetic algorithm for training dynamical object emulator based on RBF neural network. Int. J. Appl. Electromagn. Mech. (Netherlands), 9(1):65–74, 1998. †CCA43024/98 ga98aSergeev. [1680] A. Shimura and K. Yoshida. Steering control for car cornering by means of learning using neural-network and genetic algorithm. In Proceedings of the Intelligent Components for Vehicles, pages 25–28, Seville, Spain, 23.-24. March 1998. Pergamon Press ltd, Oxford. †P83398 ga98aShimura. [1681] Sigeru Omatu, Fumiaki Takeda, Saizo Onami, and Takahashi Kadono. Pattern recognition apparatus and method of optimizing mask for pattern recognition according to genetic algorithm, 1998. (U. S. patent no. 5,729,623. Issued March 17 1998; http://appft1.uspto.gov/netahtml/PTO/search-adv.html) ga98aSigeruOmatu. [1682] S. Jung and B. Ravani. Precise position control of stenciling robot manipulator using neural-network. In Proceedings of the 1998 IEEE International Conference on Systems, Man, and Cybernetics, pages 3550– 3553, San Diego, CA, 11.-14. October 1998. IEEE New York, NY. †P82602 ga98aSJung. [1683] S. Omatu and M. Yashioka. Stability of inverted pendulum by neuro-PID control with genetic algorithm. In Proceedings of the 1998 IEEE International Joint Conference on Neural Networks, pages 2142–2145, Anchorage, AK (USA), 4.-9. May 1998. IEEE, New York, NY. †CCA86052/98 ga98aSOmatu. [1684] S. Ozawa, K. Tsutsumi, and N. Baba. Design of modular neural-network architectures using genetic algorithms. In Proceedings of the Fifth International Conference on Neural Information Processing Jointly with JNNS’98: The 1998 Annual Conference of the Japanese Neural Network Society, pages 1608–1611, Kitakyushu, Japan), 21.-23. October 1998. IOS Press, Amsterdam. †P84332 ga98aSOzawa. [1685] Sebastiano Stramaglia, Guiseppe Satalino, A. Sternieri, P. Anelli, Palma N. Blonda, and Guido Pasquariello. Parallel genetic algorithm for the design of neural networks: an application to the classification 154 Genetic algorithms and neural networks of remotely sensed data. In Bruno Bosacchi, David B. Fogel, and James C. Bezdek, editors, Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation, volume SPIE-3455, pages 35–42, ?, October 1998. The International Society for Optical Engineering. * www/SPIE Web ga98aSStramaglia. [1686] A. Stafylopatis and K. Blekas. Autonomous vehicle navigation using evolutionary reinforcement learning. European Journal of Operational Research, 108(2):306–318, 16. July 1998. ga98aStafylopatis. [1687] S. Stramaglia, G. Satalino, A. Sternieri, P. Anelli, P. Blonda, and G. Pasquariello. Parallel genetic algorithm for the design of neural networks - an application to the classification of remote sensed data. In Proceedings of the Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation, pages 35–42, San Diego, CA, 20.-22. July 1998. SPIE – International Society for Optical Engineering. †P83323 ga98aStramaglia. [1688] Sung-Bae Cho. Evolutionary modular neural networks for intelligent systems. Int. J. Intell. Syst. (USA), 13(6):483–493, 1998. †CCA79357/98 ga98aSung-BaeCho. [1689] Taizo Hanai, Naoya Iwata, Hiroyuki Honda, Takeshi Furuhashi, Yoshiki Uchikawa, and Takeshi Kobayashi. Optimization of koji making process using FNN and CFGA. In Toshiomi Yoshida and Suteaki Shioya, editors, Computer Applications in Biotechnology (Proceedings of the 7th International Conference) CAB7, pages 215–218, Osaka (Japan), May 31.- June 4. 1998. IFAC Publications, Elsevier Science Ltd., Oxford (UK). †TKK/AS/Halme ga98aTaizoHanai. [1690] T. Froese. Optimizing of polymerisation processes with neural networks and genetic algorithm. Autom. tech. Prax. (Germany), 40(5):49–53, 1998. In German †CCA68134/98 ga98aTFroese. [1691] T. Fujii and S. Funabiki. Control strategy of leveling load power fluctuations based on fuzzy neural networks by tuning coefficients of learning rate with genetic algorithm. Electr. Eng. Jpn (USA), 125(1):65–72, 1998. †EEA115411/98 ga98aTFujii. [1692] T. Iba and Y. Takefuji. Adaptation of neural agent in dynamic environment - hybrid system of genetic algorithm and neural-network. In Proceedings of the 1998 Second International Conference on Knowledgebased Intelligent Electronic Systems, volume 3, pages 575–584, Adelaide, SA (Australia), 21.-23. April 1998. IEEE, New York, NY. †P82255 ga98aTIba. [1693] T. Kondo, A. Ishiguro, and Y. Uchikawa. Evolutionary construction of neural controllers using the concept of phenotypic plasticity. Trans. Soc. Instrum. Control Eng. (Japan), 34(6):648–650, 1998. In Japanese †CCA78695/98 ga98aTKondo. [1694] T. Morimoto and Y. Hashimoto. An intelligent control technique based on fuzzy controls, neural networks and genetic algorithms for greenhouse automation. In Proceedings of the 3rd IFAC/CIGR Workshop on Artificial Intelligence in Agriculture, pages 61–66, Makuhari, Japan, 24.-26. April 1998. Elsevier Science Ltd, Kidlington (UK). †CCA60179/99 ga98aTMorimoto. [1695] Thomas Ragg and Steffen Gutjahr. Neural network optimization through searching guided by stochastic methods. In H.-J. Zimmermann, editor, Proceedings of the 6th European Congress on Intelligent Techniques and Soft Computing, EUFIT’98, volume 1, pages 245–249, Aachen (Germany), 7.-10. September 1998. Verlag und Druck Mainz GmbH, Aachen (Germany). †CCA68522/99 ga98aTRagg. [1696] T. Senjyu, H. Sakihara, and K. Uezato. Deterministic prediction method using recurrent neural network optimized by genetic algorithm. Bull. Fac. Eng. Univ. Ryukyus (Japan), (55):49–59, 1998. In Japanese †CCA64607/98 ga98aTSenjyu. [1697] Vladimir Brusic, George Rudy, Marco Honeyman, Jürgen Hammer, and Leonard C. Harrison. Prediction of MHC class II-binding peptides using an evolutionary algorithm and artificial neural network. Bioinformatics, 14(2):121–130, 1998. ga98aVBrusic. [1698] D. I. Voronenko. Evolved neural systems with unit breeding. principles of development. In Proceedings of the 1998 IEEE International Joint Conference on Neural Networks, volume 1, pages 674–679, Anchorage, AK, 4.-9. May 1998. IEEE, New York, NY. †CCA84333/98 ga98aVoronenk. [1699] V. Palade, S. Bumbaru, and G. Negoita. A method for compiling neural networks into fuzzy rules using genetic algorithms and hierarchical approach. In Proceedings of the 1998 Second International Conference on Knowledge-Based Intelligent Electronic Systems, volume 2, pages 353–358, Adelaide, SA (Australia), 21.-23. April 1998. IEEE, New York, NY. †P82254 ga98aVPalade. [1700] Valceres V. R. Silva, Wael Khatib, and Peter J. Fleming. Variable complexity modelling controller design using neural networks and evolutionary computing. In Ošmera [1934], pages 290–295. ga98aVVRSilva. Bibliography 155 [1701] W. A. Farag, V. H. Quintana, and G. Lambert-Torres. A genetic-based neuro-fuzzy approach for modeling and control of dynamical systems. IEEE Transactions on Neural Networks, 9(5):756–767, 1998. †CCA76724/98 ga98aWAFarag. [1702] I. Woolley, C. Kambhampati, D. Sandoz, and K. Warwick. Intelligent control toolkit for an advanced control system. In UKACC International Conference on Control, volume 1, pages 445–450, 1998. †ChA344948g/98 ga98aWoolley. [1703] Meng Xiang-Wu and Cheng Hu. A learning algorithm of Hopfield neural network based on evolutionary programming with forgetting. J. Softw. (China), 9(2):151–155, 1998. (In Chinese) †CCA38287/98 ga98aXiang-Wu. [1704] Xin Yao and Yong Liu. Making use of population information in evolutionary artificial neural networks. IEEE Transactions on Systems, Man, and Cybernetics B, Cybernetics, 28(3):417–425, 1998. †CCA51020/98 ga98aXinYao. [1705] X. S. Lu and N. Bourbakis. Neural-network training using genetic algorithms in ATM traffic control. In Proceedings of the IEEE International Joint Symposia on Intelligence and Systems, pages 396–403, Rockville, MD (USA), 21.-23. May 1998. IEEE Computer Society Press, Los Alamitos , CA. †P80657 ga98aXSLu. [1706] Xinxing Yang and Li-Cheng Jiao. Fast global optimization fuzzy neural network and its application in data fusion. In Ji Zhou, Anil K. Jain, Tianxu Zhang, Yaoting Zhu, Mingyue Ding, and Jianguo Liu, editors, International Symposium on Multispectral Image Processing (ISMIP’98), volume SPIE-3545, pages 570– 573, ?, September 1998. The International Society for Optical Engineering. * www/SPIE Web ga98aXYang. [1707] Y. Yamamoto. A synthesis method of the approximate reasoning engine by means of genetic algorithmneural net realization of any multiple-valued logic function using GA. In Proceedings of the 1998 28th IEEE International Symposium on Multiple- Valued Logic, pages 201–208, Fukuoka, Japan, 27.-29. May 1998. IEEE Computer Society Press, Los Alamitos , CA. †CCA60736/98 ga98aYamamoto. [1708] Yanchun Liang, Wenying Gong, Xiaowei Yang, and Chunguang Zhou. Identification of nonlinear characteristics in cushioning packaging using genetic evolutionary neural networks. Mech. Res. Commun. (UK), 25(4):395–403, 1998. †CCA91935/98 ga98aYanLiang. [1709] Yong-Hua Song and A. T. Johns. Application of fuzzy logic in power systems. II comparison and integration with expert systems, neural networks and genetic algorithms. Power Engineering Journal, 12(4):185–190, 1998. †CCA82473/98 ga98aYong-HuaSong. [1710] Ni Yuanping, Zou Jinhui, and Chen Ai. Improving GA-BP strategy and pattern classification. Mini-Micro Syst. (China), 19(7):40–44, 1998. In Chinese †EEA107232/98 ga98aYuanping. [1711] Y. Watanabe and N. Mizuguchi. Solving optimization problems using mixed method of Hopfield neural network and genetic algorithm. Transactions of the Institute of Electronics, Information, and Communication Engineers D-II (Japan), J81D-II(1):156–161, 1998. In Japanese †CCA17949/98 ga98aYWatanabe. [1712] Yen-Wei Chen, X. Y. Zeng, and Zensho Nakao. A hybrid neural-network training approach of backpropagation and genetic algorithm for classification of remotely-sensed images. In Proceedings of the Fifth International Conference on Neural Information Processing Jointly with JNN’98: The 1998 Annual Conference of the Japanese Neural Network Society, pages 1402–1408, Kitakyushu, Japan, 21.-23. October 1998. IOS Press, Amsterdam. †P84332 ga98aYWChen. [1713] Zhang Yiming, Guan Xianbin, Zhang Xiaohui, and Lan Hongxiang. Distributed fuzzy neural network based on genetic algorithm. J. Fudan Univ., Nat. Sci. (China), 37(1):93–98, 1998. In Chinese †CCA58232/98 ga98aZhYiming. [1714] A. Grauel and F. Berk. Mapping of dynamical systems by recurrent neural networks in an evolutionary algorithm approach. In Proceedings of the 6th European Congress on Intelligent Techniques and Soft Computing, volume 1, pages 470–476, Aachen (Germany), 7.-10. September 1998. Verlag Mainz, Aachen (Germany). †CCA68526/99 ga98bAGrauel. [1715] A. I. Taalab, H. A. Darwish, and T. A. Kawady. ANN-based novel fault detector for generator windings protection. In IEEE Power Engineering Society Winter Meeting, volume 2, page 963, New York, NY, 31. January-4. February 1998. IEEE, Piscataway, NJ. ga98bAITaalab. [1716] Ari S. Nissinen and Heikki Hyötyniemi. Evolutionary training of behavior-based self-organizing map. In Proceedings of 1998 IEEE World Congress on Computational Intelligent (WCCI98), volume ?, pages 660–665, Anchorage, Alaska, 4.-9. May 1998. IEEE. ga98bAriNissinen. 156 Genetic algorithms and neural networks [1717] Catherine Bounsaythip and Timo Honkela. Combination of neural and evolutionary methods for data organization. In Katsumi Tanaka and Shahram Ghandeharizadeh, editors, Proceedings of the 5th International Conference on Foundations of Data Organization, pages 20–25, Kobe (Japan), 12.-13. November 1998. ? ga98bBounsaythip. [1718] Colin R. Reeves and Stewart J. Taylor. Selection of training data for neural networks by a genetic algorithm. In Agoston E. Eiben, Thomas Bäck, Marc Schoenauer, and Hans-Paul Schwefel, editors, Parallel Problem Solving from Nature - PPSN V, 5th International Conference, volume LNCS of 1498, pages 633–642, Amsterdam (The Netherlands), September 1998. Springer-Verlag Berlin Heidelberg. * www /Springer ga98bCRReeves. [1719] Du-Yih Tsai. Classification of heart diseases in ultrasonic images using neural networks trained by genetic algorithms. In Y. Baozong and T. Xiaofang, editors, 1998 Fourth International Conference on Signal Processing Proceedings. ICSP ’98, volume 2, pages 1213–1216, Beijing, China, 12.-16.October 1998. IEEE, Piscataway, NJ. * www/IEEE ga98bD-YTsai. [1720] D. Dasgupta. Evolving neuro-controllers for a dynamic system using structured genetic algorithms. Appl. Intell., Int. J. Artif. Intell. Neural Netw. Complex Probl.-Solving Technol. (Netherlands), 8(2):113–121, 1998. †CCA67639/98 ga98bDasgupta. [1721] F. Takeda. Neural network recognition system tuned by GA and application of foreign paper currencies. Transactions of the Institute of Electrical Engineers of Japan C, 118-C(5):773–780, 1998. In Japanese †CCA61731/98 ga98bFTakeda. [1722] Helmut A. Mayer. Symbiotic coevolution of artificial neural networks and training data sets. In Agoston E. Eiben, Thomas Bäck, Marc Schoenauer, and Hans-Paul Schwefel, editors, Parallel Problem Solving from Nature - PPSN V, 5th International Conference, volume LNCS of 1498, pages 511–520, Amsterdam (The Netherlands), September 1998. Springer-Verlag Berlin Heidelberg. * www /Springer ga98bHAMayer. [1723] J. C. Figueira Pujol and Riccardo Poli. Evolving the topology an the weights of neural networks using a dual representation. Appl. Intell., Int. J. Artif. Intell. Neural Netw. Complex Probl.-Solving Technol. (Evolutionary), 8(1):73–84, 1998. †CCA43110/98 ga98bJCFPujol. [1724] L. M. Brasil, F. M. De Azevedo, J. M. Barreto, and M. Noirhomme-Fraiture. Training algorithm for neurofuzzy-GA systems. In Proceedings of the 16th IASTED International Conference, pages 45–47, Germany, 23.-25. February 1998. IASTED/ACTA Press, Anaheim, CA (USA). †CCA86511/99 ga98bLMBrasil. [1725] I. Nagayama and M. Kudaka. Automatic detection of histological components in breast cancer image by using genetic neural network. In Proceedings of the 5th International Conference on soft Computing and Information/Intelligent Systems, volume 2, pages 1011–1016, Fukuoka, Japan, 16.-20. October 1998. World Scientific, Singapore. †CCA75235/99 ga98bNagayama. [1726] D. Rutkowska. Fuzzy-neural-GA systems with different defuzzification methods. In Proceedings of the 6th European Congress on Intelligent Techniques and Soft computing, volume 1, pages 713–717, Aachen (Germany), 7.-10. September 1998. Verlag Mainz, Aachen (Germany). †CCA77444/99 ga98bRutkowska. [1727] S. Y. Liong, S. T. Khu, and W. T. Chan. Novel application of genetic algorithm and neural network in water resources: Development of Pareto front. In ?, editor, Proceedings of the 11th Cogress IAHR-APD, pages 185–194, Yogyakarta (Indonesia), ? 1998. ? †[1937] ga98bSYLiong. [1728] Tomonobu Senjyu, Shotaro Yamane, and Katsumi Uezato. Improvement of multi-machine power system stability by variable series capacitor (VSrC) using neural network. In IEEE Power Engineering Society Winter Meeting, volume 1, pages 628–633, New York, NY, 31. January-4. February 1998. IEEE, Piscataway, NJ. ga98bTSenjyu. [1729] W. M. Jenkins. Genetic-based structural design optimization with reanalysis by neural networks. In Proceedings of the Advances Engineering Computational Technology, pages 221–228, Edinburgh, Scotland, 18.-21. August 1998. Civil Comp. Press, Edingburgh. †P82882 ga98bWMJenkins. [1730] Xin Yao and Yong Liu. Towards designing artificial neural networks by evolution. Applied Mathematics and Computation, 91(1):83–90, April 1998. ga98bXinYao. [1731] Ari S. Nissinen, Heikki Hyötyniemi, and Heikki N. Koivo. Evolutionary SOM for generation of classifier maps. In ?, editor, Proceedings of Annual Conference of ICIMS-NOE, volume ?, pages 240–245, Bremen (Germany), 14.-17. May 1998. ? ga98cAriNissinen. [1732] Minoru Fukumi, Toshiki Yoshino, and Norio Akamatsu. Designing a neural network using a genetic algorithm with deterministic mutation and partial fitness. Journal of Intelligent and Fuzzy Systems, 6(1):17–25, ? 1998. * http://iospress.metapress.com ga98cMFukumi. Bibliography 157 [1733] Mitsuo Gen, K. Ida, R. Kobuchi, and C. Lee. Hybridized neural-network and genetic algorithms for solving nonlinear integer programming. In Proceedings of the 1998 Second International Conference on Knowledge-Based Intelligent Electronic Systems, pages 272–277, Adelaide (Australia), 21.-23. April 1998. IEEE, New York, NY. †P82254 ga98cMGen. [1734] Sung-Bao Cho. Behavioral analysis of modular neural networks developed by evolutionary mechanism. J. KISS(B), Softw. Appl. (South Korea), 25(3):417–425, 1998. In Korean †CCA61828/98 ga98cSung-BaeCho. [1735] Tomonobu Senjyu, Toyohiro Arakaki, and Katsumi Uezato. Stabilization control for multi-machine power system by nonlinear state feedback control using neural network. In IEEE Power Engineering Society Winter Meeting, volume 1, pages 622–627, New York, NY, 31. January-4. February 1998. IEEE, Piscataway, NJ. ga98cTSenjyu. [1736] Sung-Bae Cho and K. Shimohara. Cooperative behavior in evolved modular neural networks. In Proceedings of the 5th International Conference on Soft Computing and Information/Intelligent Systems, volume 2, pages 606–609, Fukuoka, Japan, 16.-20. October 1998. World Scientific, Singapore. †CCA68413/99 ga98dSung-BaeCho. [1737] Antonio Concilio, Luciano de Vivo, and A. Sorrentino. Architecture definition of a piezoceramic-based ANN system for multiple-tone vibration suppression. In Norman M. Wereley, editor, Smart Structure and Integrated Systems, volume SPIE-3668, pages 250–261, ?, June 1999. The International Society for Optical Engineering. * www/SPIE Web ga99aAConcilio. [1738] Alaa H. Aly and Richard C. Peralta. Optimal design of aquifer cleanup systems under uncertainty using a neural network and a genetic algorithm. Water Resources Research, 35(8):2523–2532, August 1999. †NASA ADS ga99aAHAly. [1739] A. Hugget, P. Sebastian, and J.-P. Nadeau. Global optimization of a dryer by using neural networks and genetic algorithms. AIChE J., 45(6):1227–1238, 1999. †ga01aTDiveux ChA33374/99 ga99aAHugget. [1740] A. I. Taalab, H. A. Darwish, and T. A. Kawady. ANN-based novel fault detector for generator windings protection. IEEE Transactions on Power Delivery, 14(3):824–830, July 1999. ga99aAITaalab. [1741] A. J. Ijspeert Ecole. Evolution of neural controllers for salamander-like locomotion. In Proceedings of the Sensor Fusion and Decentralized Control in Robotic Systems II, volume SPIE-3839, Boston, MA, 19.20. September 1999. SPIE. † ga99aAJIEcole. [1742] Auke J. Ijspeert. Evolution of neural controllers for salamanderlike locomotion. In Gerard T. McKee and Paul S. Schenker, editors, Sensor Fusion and Decentralized Control in Robotic System II, volume SPIE3839, pages 168–179, ?, August 1999. The International Society for Optical Engineering. * www/SPIE Web ga99aAJIjspeert. [1743] A. Kumar and V. C. Hand. Using genetic algorithms and neural-networks to predict and optimize coated board brightness. In Proceedings of the Preparing for the Next Millenium, volume 1-3, pages 161–170, Atlanta, GA, 1.-4. March 1999. Tappi Press, Atlanta. †P84360 ga99aAKumar. [1744] Igor Aleksander. Evolutionary checkers. ga99aAleksander. Nature, 402(6764):857,859–860, 23./30. December 1999. [1745] A. M. Sharif. Neural and evolutionary computing in finite element analysis. J. Comput. Inf. Technol. CIT (Croatia), 7(2):137–151, 1999. †CCA80330/99 ga99aAMSharif. [1746] A. Berlanga, P. Isasi, A. Sanchis, and J. M. Molina. Neural networks robot controller trained with evolution strategies. In Proceedings of the 1999 Congress on Evolutionary Computation-CEC99, volume 1, pages 413–419, Washington, DC, 6.-9. July 1999. IEEE, Piscataway, NJ. †CCA85438/99 ga99aBerlanga. [1747] Bahram Ghaffarzadeh Kermani, Susan S. Schiffman, and H. Troy Nagle. Using neural networks and genetic algorithms to enhance performance in an electronic nose. IEEE Transactions on Biomedical Engineering, 46(4):429–439, April 1999. ga99aBGKermani. [1748] Bin Zheng, Yuan-Hsiang Chang, Xiao-Hui Wang, and Walter F. Good. Comparison of artificial neural network and Bayesian belief network in a computer-assisted diagnosis scheme for mammography. In Proceedings of the 1999 International Joint Conference on Neural Networks (IJCNN’99), volume 6, pages 4181–4185, ?, ? 1999. IEEE, Piscataway, NJ. ga99aBinZheng. [1749] Beatrice Lazzerini, Leonardo M. Reyneri, and Marcello Chiaberge. A neuro-fuzzy approach to hybrid intelligent control. IEEE Transactions on Industry Applications, 35(2):413–425, March/April 1999. ga99aBLazzerini. [1750] Bernhard Sendhoff and Martin Kreutz. Variable encoding of modular neural networks for time series prediction. In V. W. Porto, editor, Congress on Evolutionary Computation, volume 1, pages 259–266, New York, ? 1999. IEEE Press. ga99aBSendhoff. 158 Genetic algorithms and neural networks [1751] Chin-Shyurng Fahn, Kou-Torng Lan, and Zen-Bang Chern. Fuzzy rules generation using new evolutionary algorithms combined with multilayer perceptrons. IEEE Transactions on Industrial Electronics, 46(6):1103–1113, December 1999. ga99aC-SFahn. [1752] Craig A. Jensen, Russell D. Reed, Robert J. Marks, II, Mohamed A. El-Sharkawi, Jae-Byung Jung, Robert T. Miyamoto, Gregory M. Andersen, and Christian J. Eggen. Inversion of feedforward neural networks: algorithms and applications. Proceedings of the IEEE, 87(9):1536–1549, September 1999. ga99aCAJensen. [1753] Chi C. Hung, Venkata Atluri, and Tommy L. Coleman. Combined genetic K-means and radial basis function neural network technique for classifying and predicting soil moisture. In Giovanna Cecchi, Edwin T. Engman, and Eugenio Zilioli, editors, Remote Sensing for Earth Science, Ocean and Sea Ice Applications, volume SPIE-3868, pages 12–15, ?, December 1999. The International Society for Optical Engineering. * www/SPIE Web ga99aCCHung. [1754] N. Chaiyaratana and A. M. S. Zalzala. Hybridisation of neural networks and genetic algorithms for timeoptimal control. In Proceedings of the 1999 Congress on Evolutionary Computational-CEC99, volume 1, pages 389–396, Washington, DC, 6.-9. July 1999. IEEE, Piscataway, NJ. †CCA79974/99 ga99aChaiyara. [1755] Cheng-Jian Lin. Reinforcement learning for GA-based neural networks. J. Chin. Inst. Electr. Eng. (Taiwan), 6(2):141–156, 1999. †CCA86488/99 ga99aChengLin. [1756] Chia-Ju Wu. Genetic tuning of PID controllers using a neural network model: a seesaw example. J. Intell. Robot. Syst. Theory Appl. (Netherlands), 25(1):43–59, 1999. †CCA69796/99 ga99aChia-JWu. [1757] Chi-Sun Joung, Dong Wook Lee, Hyo-Byung Jun, and Kwee Bo Sim. Evolution of neural network’s structure and learning patterns based on competitive co-evolutionary method. J. Inst. Electron. Eng. Korea S (South Korea), 36-S(1):29–37, 1999. In Korean †CCA53479/99 ga99aChiJoung. [1758] Chin-Teng Lin and Chong-Ping Jou. Controlling chaos by GA-based reinforcement learning neural network. IEEE Transactions on Neural Networks, 10(4):846–859, July 1999. ga99aChin-TengLin. [1759] Chen Wenxia, Zhang Yu, and Zheng Junli. Link capacity control of ATM using genetic neural network algorithm. J. Tsinghua Univ., Sci. Technol. (China), 39(1):30–33, 1999. In Chinese †CCA59492/99 ga99aChWenxia. [1760] P. A. Creaser and B. Stacey. Evolutionary generation of artificial neural network based guidance laws. In Proceedings of the European Control Conference, Karlsruhe, Germany, 31. August- 3. September 1999. VDI-Verlag. † ga99aCreaser. [1761] Daniel Polani. (overview of genetic algorithms in som). In Erkki Oja and Samuel Kaski, editors, Kohonen Maps, pages 157–169. Elsevier, Amsterdam, 1999. ga99aDanielPolani. [1762] DaeEun Kim and Jaehong Park. Frequency selection with oscillatory neurons for engine misfire detection. In International Joint Conference on Neural Networks (IJCNN), volume 4, pages 2649–2652, Washington, DC, USA, 10.-16.July 1999. IEEE, Piscataway, NJ. * www/IEEE ga99aDKim. [1763] Dong-Wook Lee and Kwee Bo Sim. Evolving chaotic neural systems for time series prediction. In Proceedings of the 1999 Congress on Evolutionary Computation-CEC99, volume 1, pages 310–316, Washington, DC, 6.-9. July 1999. IEEE, Piscataway, NJ. †CCA81095/99 ga99aDong-Lee. [1764] E. D. De Jong and L. Steels. Generation and selection of sensory channels. In Proceedings of the First European Workshops, pages 90–100, Goteburg, Sweden, 26.-27. May 1999. Springer-Verlag, Berlin (Germany). †CCA77888/99 ga99aEDDeJong. [1765] E. Gómez-Ramı́rez, S. Soltani, A. González-Yunes, and M. Avila-Alvarez. Mejoramiento del proceso de aprendizaje para la predicción de series de tiempo empleando filtrado multirresolución en redes neuronales artificiales polinomiales [Improving learning process for identification with multiresolution filtering in polynomial artificial neural networks]. In ?, editor, Segundo Encuentro de Computación, ENC’99, page ?, Pachua?, 12.-15. September 1999. ? (in Spanish; in English as [1846]) ga99aEGomez-Ramirez. [1766] E. M. Iyoda, L. N. deCastro, F. Gomide, and F. J. Von Zuben. Evolutionary design of neurofuzzy networks for pattern classification. In Proceedings of the 1999 Congress on Evolutionary Computation-CEC99, volume 2, pages 1237–1244, Washington, DC, 6.-9. July 1999. IEEE, Piscataway, NJ. †CCA82133/99 ga99aEMIyoda. [1767] E. S. Yu and E. D. Liddy. Feature selection in text categorization using the Baldwin effect. In Proceedings of the International Joint Conference on Neural Networks (IJCNN’99), volume 4, pages 2924–2927, Washington DC, 10.-16. July 1999. IEEE, Piscataway, NJ. * www /IEEE ga99aESYu. Bibliography 159 [1768] Arthur Filippidis, L. C. Jain, and Noel M. Martin. Using genetic algorithms and neural networks for surface land mine detection. IEEE Transactions on Signal Processing, 47(1):176–186, January 1999. ga99aFilippidis. [1769] Fabrizio Russo. Evolutionary neural fuzzy systems for noise cancellation in image data. IEEE Transactions on Instrumentation and Measurement, 48(5):915–920, October 1999. ga99aFRusso. [1770] W. Golubski and T. Feuring. Genetic algorithm-based neural-network initialization. In Proceedings of the Computational Intelligence for Modelling, Control & Automation - Neural Networks & Advanced Control Strategies, pages 196–201, Vienna, Austria, 17.-19. February 1999. IOS Press, Amsterdam. †P84321 ga99aGolubski. [1771] G. P. Liu and V. Kadirkamanathan. Multiobjective criteria for neural network structure selection and identification of nonlinear systems using genetic algorithms. IEE Proc., Control Theory Appl. (UK), 146(5):373–382, 1999. †CCA94450/99 ga99aGPLiu. [1772] Geza Szekely, Mary Lou Padgett, and Gerry Dozier. Automated parameter adaptation in pulse-coupled neural networks for spatially distributed sensors. In Firooz A. Sadjadi, editor, Automatic Target Recognition IX, volume SPIE-3718, pages 549–554, ?, August 1999. The International Society for Optical Engineering. * www/SPIE Web ga99aGSzekely. [1773] G. Zihua and O. C. Au. Map automatic input based on NN and GAs. In Proceedings of the 1999 IEEE International Symposium on Circuits and Systems VLSI, volume 2, pages 306–309, Orlando, FL, 30. may2. jun ? 1999. IEEE, Piscataway, NJ. †CCA102877/99 ga99aGZihua. [1774] H. A. Mayer and R. Schwaiger. Evolutionary and coevolutionary approaches to time series prediction using generalized multi-layer perceptrons. In Proceedings of the 1999 Congress on Evolutionary Computation-CEC99, volume 1, pages 275–280, Washington D.C., 6.-9. July 1999. IEEE, Piscataway, NJ. †CCA84338/99 ga99aHAMayer. [1775] Hugo de Garis, A. Buller, M. Korkin, F. Gers, N. E. Nawa, and M. Hough. ATR’s artificial brain (“CAMBrain”) project: A sample of what individual “CoDi-1 Bit” model evolved neural net modules can do with digital and analog I/O. In Proceedings of the First NASA/DoD Workshop on Evolvable Hardware, pages 102–110, Pasadena, CA, 19.-21. July 1999. IEEE Computer Society Press, Los Alamitos , CA. †CCA77455/99 ga99aHdeGaris. [1776] Hamid Ghezelayagh and Kwang Y. Lee. Training neuro-fuzzy boiler identifier with genetic algorithm and error back-propagation. In IEEE Power Engineering Society Summer Meeting, volume 2, pages 978–982, Edmonton, Alta. (Canada), 18.-22. July 1999. IEEE, Piscataway, NJ. ga99aHGhezelayagh. [1777] Hsiang-Yin Chen, Ta-Cheng Chen, David I. Min, Gary W. Fischer, and You-Min Wu. Prediction of tacrolimus blood levels by using the neural network with genetic algorithm in liver transplantation patients. Therapeutic Drug Monitoring, 21(1):50–56, February 1999. * AHA ga99aHsiang-YinChen. [1778] Huang Yuan, Shian-Shyong Tseng, Wu Gangshan, and Zhang Fuyan. A two-phase feature selection method using both filter and wrapper. In Proceedings of the 1999 IEEE International Conference on Systems, Man, and Cybernetics (SMC’99), volume 2, pages 132–136, Tokyo (Japan), 12.-15. October 1999. IEEE, Piscataway, NJ. ga99aHuangYuan. [1779] Jon A. Benediktsson and Helgi Benediktsson. Neuro-fuzzy and soft computing in classification of remote sensing data. In Sebastiano B. Serpico, editor, Image and Signal Processing for Remote Sensing V, volume SPIE-3871, pages 176–187, ?, December 1999. The International Society for Optical Engineering. * www/SPIE Web ga99aJABenediktsson. [1780] J. C. Cassa, G. Floridia, A. R. Souza, and R. T. Oliveira. Prediction of cement paste mechanical behaviour from chemical composition using genetic algorithms and artificial neural networks. In Proceedings of the Second International Conference on Intelligent Processing and Manufacturing of Materials, volume 1, pages 291–298, Honolulu, HI (USA), 10.-15. July 1999. IEEE, Piscataway, NJ. †CCA102353/99 ga99aJCCassa. [1781] J. F. D. Addison, S. Wermter, and J. MacIntyre. Effectiveness of feature extraction in neural networks architectures for novelty detection. In ICANN 99. Ninth International Conference on Artificial Neural Networks, volume 2, pages 976–981, Edinburgh, UK, 7.-10.September 1999. IEEE, Piscataway, NJ. * www/IEEE ga99aJFDAddison. [1782] Jennifer Hallinan and Paul Jackway. Co-operative evolution of a neural classifier and feature subset. In B. McKay, X. Yao, C. S. Newton, J.-H. Kim, and T. Furuhashi, editors, Simulated Evolution and Learning, Second Asia-Pacific Conference on Simulated Evolution and Learning, SEAL’98, volume LNAI of 1585, pages 397–404, Canberra (Australia), November 1999. Springer-Verlag Berlin Heidelberg. * www /Springer ga99aJHallinan. 160 Genetic algorithms and neural networks [1783] J. Hunger and G. Huttner. Optimization and analysis of force field parameters by combination of genetic algorithms and neural networks. J. Comput. Chem., 20(4):455–471, ? 1999. * ChA 287159v/99 ga99aJHunger. [1784] Jinn-Moon Yang, Jorng-Tzong Horng, and Cheng-Yen Kao. Incorporation family competition into Gaussian and Cauchy mutations to training neural networks using an evolutionary algorithm. In Proceedings of the 1999 Congress on Evolutionary Computation-CEC99, volume 3, pages 1994–2001, Washington D.C., 6.-9. July 1999. IEEE, Piscataway, NJ. †CCA77481/99 ga99aJinnYang. [1785] Jong Hwa Lim, Doo Hyun Choi, and Chan Sik Hwang. A new evolutionary programming algorithm using the learning rule of a neural network for mutation of individuals. J. Inst. Electron. Eng. Korea C (South Korea), 36-C(3):58–64, 1999. In Korean †CCA60903/99 ga99aJongHLim. [1786] Jr V. Pilla and H. S. Lopes. Evolutionary training of a neurofuzzy network for detection of p wave of the ecg. In Proceedings of the Third International Conference on computational Intelligence and Multimedia Applications, pages 102–106, New Delhi, India, 23.-26. September 1999. IEEE Computer Society Press, Los Alamitos , CA. †CCA93085/99 ga99aJrVPilla. [1787] J. V. Hansen, J. B. McDonald, and R. D. Nelson. Time series prediction with genetic-algorithm designed neural network: An empirical comparison with modern statistical models. Comput. Intell. (USA), 15(3):171–184, 1999. †CCA78213/99 ga99aJVHansen. [1788] Kazuhiro Matsui, Yusuke Suganami, and Yukio Kosugi. Feature selection by genetic algorithm for MRI segmentation. Systems and Computers in Japan, 30(7):69–78, 1999. (Translation from Denshi Joho Tsushin Gakkai Ronbunshi, Vol. J80-D-II, No. 7, July 1997, pp. 1712-1721) †CCA66636/99 ga99aKazuhiroMatsui ⇒ http://www3.interscience.wiley.com/journal/61500346/abstract?CRETRY=1&SRETRY=0. [1789] Kim Wing C. Ku, Man Wai Mak, and Wan Chi Siu. Adding learning to cellular genetic algorithms for training recurrent neural networks. IEEE Transactions on Neural Networks, 10(2):239–252, March 1999. ga99aKimWingCKu. [1790] Gregor Kjellström. The evolution in the brain. Applied Mathematics and Computation, 98(2-3):293–300, February 1999. ga99aKjellstrom. [1791] Teuvo Kohonen. Fast evolutionary learning with batch-type self-organizing maps. Neural Processing Letters, 9(2):153–162, April 1999. †CCA 68477/99 ga99aKohonen. [1792] L. C. Jain. Special section on fusion of neural nets, fuzzy systems, and genetic algorithms in industrial applications. IEEE Transactions on, 46(6):1049–1050, December 1999. ga99aLCJain. [1793] Srinivasa Lingireddy and Lindell E. Ormsbee. chapter 3. Neural networks in optimal calibration of water distribution systems, pages 53–76. American Society of Civil Engineers, Reston, VA, 1999. ga99aLingireddy. [1794] Lin He, Ke-Jun Wang, Hong-Zhong Jin, Guo-Bin Li, and X. Z. Gao. The combination and prospects of neural networks, fuzzy logic and genetic algorithms. In Proceedings of the 1999 IEEE Midnight - Sun Workshop on Soft Computing Methods in Industrial Applications, pages 52–57, Kuusamo (Finland), 16.18. June 1999. IEEE, Piscataway, NJ. †CCA68494/99 ga99aLinHe. [1795] Liqun Han. Neural network modeling and genetic algorithm for optimizing formulation of catalysts. Huagong Xuebao (Chin. Ed.), 50(4):500–504, 1999. †ChA172151/99 ga99aLiqunHan. [1796] L. L. Lai, H. Subasinghe, N. Rajkumar, E. Vaseekar, B. J. Gwyn, and V. K. Sood. Object-oriented genetic algorithm based artificial neural networks for load forecasting. In B. McKay, X. Yao, C. S. Newton, J.-H. Kim, and T. Furuhashi, editors, Simulated Evolution and Learning, Second Asia-Pacific Conference on Simulated Evolution and Learning, SEAL’98, volume LNAI of 1585, pages 462–470, Canberra (Australia), November 1999. Springer-Verlag Berlin Heidelberg. * www /Springer ga99aLLLai. [1797] Luonan Chen and K. Aihara. Global searching ability of chaotic neural networks. IEEE Trans. Circuits Syst. I, Fundam. Theory Appl. (USA), 46(8):974–993, 1999. †CCA77451/99 ga99aLuonanChen. [1798] Mahmoud A. Taha, Azza M. Abou-Zeid, Awad S. Hanna, and Jeffrey S. Russell. chapter 10. Merging genetic algorithms with neural networks: owner-contractor prequalification example, pages 247–259. American Society of Civil Engineers, Reston, VA, 1999. ga99aMATaha. [1799] Meifen Cao and A. Kawamura. A design scheme of neural oscillatory networks by hierarchical evolutionary calculation for generation of humanoid biped walking patterns. Adv. Robot. (Netherlands), 12(7-8):697–710, 1999. †CCA70966/99 ga99aMeifenCao. Bibliography 161 [1800] Martin Kreutz, Anja M. Reimetz, Bernhard Sendhoff, Claus Weihs, and Werner von Seelen. Structure optimisation of density estimation models applied to regression problems with dynamics noise. In D. Heckerman and J. Whittaker, editors, Artificial Intelligence and Statistics 99: Proceedings of the 7th International Workshop, volume ?, pages 237–242, San Mateo, CA, January 1999. Morgan Kauffman Publishers. ga99aMKreutz. [1801] Masahiro Murakawa, Shuji Yoshizawa, Isamu Kajitani, Xin Yao, Nobuki Kajihara, Masaya Iwata, and Tetsuya Higuchi. The GRD chip: Genetic Reconfiguration of DSPs for neural networks processing. IEEE Transactions on Computers, 48(6):628–639, June 1999. ga99aMMurakawa. [1802] M. Moechtar, A. S. Farag, L. Hu, and T. C. Cheng. Combined genetic algorithms and neural-network approach for power system transient stability evaluation. Eur. Trans. Electr. Power (Germany), 9(2):115– 122, 1999. †CCA59269/99 ga99aMoechtar. [1803] Masato Onishi, Wataru Funakoshi, and Masanori Ozawa. Network topology designing device, network topology designing method and recording medium stored with network topology design program, 1999. (JP patent no. 11345257. Issued December 14 1999) * fi.espacenet.com ga99aMOnishi. [1804] Moritoshi Yasunaga, Taro Nakamura, and Ikuo Yoshihara. Sonar spectrum recognition chip designed by evolutionary algorithm. In Proceedings of the International Joint Conference on Neural Networks (IJCNN’99), volume 5, pages 3182–3187, Washington DC, 10.-16. July 1999. IEEE, Piscataway, NJ. * www /IEEE ga99aMoritoshiYasunaga. [1805] M. Turkoglu, I. Aydin, M. Murray, and A. Sakr. Modeling of a roller-compaction process using neural networks and genetic algorithms. Eur. J. Pharm. Biopharm., 48(3):239–245, November 1999. * PubMed10612035 ga99aMTurkoglu. [1806] Masashi Yamaguchi. Optimization method for fuzzy neural network, 1999. (JP patent no. 11328144. Issued November 30 1999) * fi.espacenet.com ga99aMYamaguchi. [1807] Mengjie Zhang and Victor Ciesielski. Using back propagation algorithm and genetic algorithm to train and refine neural networks for object detection. In Trevor Bench-Capon, Giovanni Soda, and A. Min Tjoa, editors, Database and Expert Systems Applications, 10th International Conference, DEXA’99, volume LNCS of 1677, pages 626–635, Florence (Italy), August/September 1999. Springer-Verlag Berlin Heidelberg. * www /Springer ga99aMZhang. [1808] P. A. Castillo, V. Rivas, J. J. Merelo, J. Gonzalez, A. Prieto, and G. Romero. G-Prop-II: global optimization of multilayer perceptrons using GAs. In Proceedings of the 1999 Congress on Evolutionary Computation-CEC99, volume 3, pages 2022–2027, Washington, DC, 6.-9. July 1999. IEEE, Piscataway, NJ. †CCA82141/99 ga99aPACastillo. [1809] F. Pasemann, U. Steinmetz, and U. Dieckman. Evolving structure and function of neurocontrollers. In Proceedings of the 1999 Congress on Evolutionary Computation-CEC99, volume 3, pages 1973–1978, Washington, DC, 6.-9. July 1999. IEEE, Piscataway, NJ. †CCA77480/99 ga99aPasemann. [1810] Roger A. Browse, Talib S. Hussain, and Matthew B. Smillie. Using attribute grammars for the genetic selection of backpropagation networks for character recognition. In Applications of Artificial Neural Networks in Image Processing IV, volume SPIE-3647, pages 26–34, San Jose, CA, 28.-29. January 1999. The International Society for Optical Engineering, Bellingham, WA. †CCA94630/99 ga99aRABrowse. [1811] Russell D. Reed and Robert J. Marks, II. Chapter 11. Genetic algorithms and neural networks, pages 185–195. MIT Press, Cambridge, MA, 1999. †TKKpaa ga99aRDReed. [1812] R. E. King, V. Goggos, and A. Stathaki. Evolutionary computation in the design of optimised neural controllers. In Proceedings of the European Control Conference, Karlsruhe, Germany, 31. August- 3. September 1999. VDI-Verlag. † ga99aREKing. [1813] Raul E. Torrez Muniz. Biologically based neural network for mobile robot navigation. In Howie M. Choset, Douglas W. Gage, Pushkin Kachroo, Mikhail A. Kourjanski, and Marten J. de Vries, editors, Mobile Robots XIII and Intelligent Transportation Systems, volume SPIE-3525, pages 285–295, ?, January 1999. The International Society for Optical Engineering. * www/SPIE Web ga99aRETorrezMuniz. [1814] R. S. T. Lee and J. N. K. Liu. An oscillatory elastic graph matching model for recognition of offline handwritten Chinese characters. In The International Conference on Knowledge-Based Intelligent Information Engineering Systems, pages 284–287, Adelaide, SA (Australia), 31. August-1. September 1999. IEEE, Piscataway, NJ. * www /IEEE ga99aRSTLee. [1815] Randall S. Sexton, Robert E. Dorsey, and John D. Johnson. Optimization of neural networks: A comparative analysis of the genetic algorithm and simulated annealing. European Journal of Operational Research, 114(3):589–601, 1. May 1999. ga99aSexton. 162 Genetic algorithms and neural networks [1816] Steven Hobday, Roger Smith, and Joe BelBruno. Applications of genetic algorithms and neural networks to interatomic potentials. Nucl. Instrum. Methods Phys. Res., Sect. B, 153(1-4):247–263, 1999. †ChA106939/99 ga99aSHobday. [1817] Shu-Heng Chen and Chun-Fen Lu. Would evolutionary computation help in designs of ANNs in forecasting foreign exchange rates? In Proceedings of the 1999 Congress on Evolutionary Computation-CEC99, volume 1, pages 267–274, Washington, DC, 6.-9. July 1999. IEEE, Piscataway, NJ. †CCA78344/99 ga99aShu-WengChen. [1818] Sunan Huang and Wei Ren. Use of neural fuzzy networks with mixed genetic/gradient algorithm in automated vehicle control. IEEE Transactions on Industrial Electronics, 46(6):1090–1102, December 1999. ga99aSHuang. [1819] Sankar Kumar Nath, Subrata Chakraborty, Sanjiv Kumar Singh, and Nilanjan Ganguly. Velocity inversion in cross-hole seismic tomography by counter-propagation neural network, genetic algorithm and evolutionary programming techniques. Geophysical Journal International, 138(1):108–124, July 1999. †NASA ADS ga99aSKNath. [1820] Sung-Bae Cho. Pattern recognition with neural networks combined by genetic algorithm. Fuzzy Sets and Systems, 103(2):339–347, 16. April 1999. ga99aSung-BaeCho. [1821] Taizo Hanai, Hiroyuki Honda, Eiji Ohkusu, Toshihiko Ohki, Hisao Tohyama, Takahiro Muramatsu, and Takeshi Kobayashi. Application of an artificial neural network and genetic algorithm for determination of process orbits in the koji making process. Journal of Bioscience and Bioengineering, 87(4):507–512, 16. January 1999. ga99aTaizoHanai. [1822] T. Kondo, A. Ishiguro, S. Tokura, Y. Uchikawa, and P. Eggenberger. Realization of robust controllers in evolutionary robotics: a dynamically-rearranging neural network approach. In Proceedings of the 1999 Congress on Evolutionary Computation-CEC99, volume 1, pages 366–373, Washington, DC, 6.-9. July 1999. IEEE, Piscataway, NJ. †CCA79789/99 ga99aTKondo. [1823] T. Kumagai, M. Wada, R. Hashimoto, and A. Utsugi. Dynamical control by recurrent neural networks through genetic algorithms. Int. J. Adapt. Control Signal Process. (UK), 13(4):261–271, 1999. †CCA78981/99 ga99aTKumagai. [1824] Teo Lian Seng, Marzuki Bin Khalid, and Rubiyah Yusof. Tuning of a neuro-fuzzy controller by genetic algorithm. IEEE Transactions on System, Man, and Cybernetics, 29(2):226–236, April 1999. ga99aTLSeng. [1825] T. Marcu, L. Ferariu, L. Mirea, and P. M. Frank. Genetic evolving of dynamic neural networks with application to process fault diagnosis. In Proceedings of the European Control Conference, Karlsruhe, Germany, 31. August- 3. September 1999. VDI-Verlag. † ga99aTMarcu. [1826] Tatyana Baidyk and Ernst Kussul. Application of genetic algorithms to optimization of neuronet recognition devices. Cybernetics and Systems Analysis, 35(5):700–707, September-October 1999. †ISI ga99aTNBaidyk. [1827] Tom Brotherton, T. Chadderdon, and Paul Grabill. Automated rule extraction for engine vibration analysis. In Proceedings of the 1999 IEEE Aerospace Conference, volume 3, pages 29–38, Aspen, CO, 6.-13. March 1999. IEEE, Piscataway, NJ. * A99-43330 ga99aTomBrotherton. [1828] T. Senjyu, Y. Kohagura, and K. Uezato. Robust control of power systems using genetic algorithm (GA) and neural network (NN). Bull. Fac. Eng. Univ. Ryukyus (Japan), (57):109–116, 1999. In Japanese †CCA54761/99 ga99aTSenjyu. [1829] Tae Seon Kim and Gary S. May. Optimization of via formation in photosensitive dielectric layers using neural networks and genetic algorithms. IEEE Transactions on Electronics Packing Manufacturing, 22(2):128–136, April 1999. ga99aTSKim. [1830] V. Pilla Jr and H. S. Lopes. Evolutionary training of a neurofuzzy network for detection of P wave of the ECG. In Proceedings of the Third International Conference on computational Intelligence and Multimedia Applications, pages 102–106, New Delhi, India, 23.-26. September 1999. IEEE Computer Society Press, Los Alamitos, California. †CCA93085/99 ga99aVPilla. [1831] Wing Yiu Choy. Using numerical methods and artificial intelligence in NMR data processing and analysis. PhD thesis, McGill University, 1999. * www /UMI ga99aWingYiuChoy. [1832] W. Sasaki, H. Uichida, and K. Takahashi. Application of self-organized genetic algorithms to a novel color recognition system of all-optical neural network. In Proceedings of the Intelligent Systems in Design and Manufacturing II, volume SPIE-3833, Boston, MA, 21.-22. September 1999. SPIE. † ga99aWSasaki. Bibliography 163 [1833] Xiao-Hui Wang, Bin Zheng, Yuan-Hsiang Chang, and Walter F. Good. Optimizing the feature set for a Bayesian network for breast-cancer diagnosis, by using genetic algorithm techniques. In Proceedings of the Society of Photo-Optical Instrumentation Engineers, volume SPIE-3661, pages 1574–1580, San Diego, CA, 22.-25. February 1999. SPIE – International Society for Optical Engineering, Bellingham. †P85053 ga99aXHWang. [1834] Xiao-Wei Zhao. Prediction of melting points of organic compounds using artificial neural network trained with the combination of genetic algorithm and gradient method. oxiao Huaxue Gongcheng Xuebao Games Econ. Behav., 13(4):299–302, 1999. †ChA204899/99 ga99aXiao-WeiZhao. [1835] Xin Yao and Yong Liu. Neural networks for breast cancer diagnosis. In Proceedings of the 1999 Congress on Evolutionary Computation-CEC99, volume 3, pages 1760–1767, Washington D.C., 6.-9. July 1999. IEEE, Piscataway, NJ. †CCA84613/99 ga99aXinYao. [1836] Y.-S. Yeun, K.-H. Lee, and Y.-S. Yang. Function approximations by coupling neural networks and genetic programming trees with oblique decision trees. Artificial Intelligence in Engineering (UK), 13(3):223–239, 1999. †CCA71080/99 ga99aY-SYeun. [1837] Yao hua He, Zhi zhong Xia, and Ben Hua. Optimization of system with non-mechanism model based on NN-GA approach. Shiyou Huagong, 28(6):372–380, 1999. †ChA230518/99 ga99aYao-huaHe. [1838] Yakov A. Pachepsky, Dennis J. Timlin, and Lajpat R. Ahuja. Estimating saturated soil hydraulic conductivity using water retention data and neural networks. Soil Science, 164(8):552–560, August 1999. * AHA ga99aYAPachepsky. [1839] I. Yoshihara, M. Numata, K. Sugawara, S. Yamada, and K. Abe. Time series prediction model building with BP-like parameter optimization. In Proceedings of the 1999 Congress on Evolutionary Computation-CEC99, volume 1, pages 295–301, Washington D.C., 6.-9. July 1999. IEEE, Piscataway, NJ. †CCA82131/99 ga99aYoshihara. [1840] Yuan-Hsiang Chang, Bin Zheng, Xiao-Hui Wang, and Walter F. Good. Computer-assisted diagnosis of breast cancer using artificial neural networks: Comparison of backpropagation and genetic algorithm. In Proceedings of the 1999 International Joint Conference on Neural Networks (IJCNN’99), volume 5, pages 3674–3679, ?, ? 1999. IEEE, Piscataway, NJ. ga99aYuan-HsiangChang. [1841] Ivan Zelinka and Jouni Lampinen. An evolutionary learning algorithms for neural networks. In Proceedings of the 5th International Conference on Soft Computing, pages 410–414, Brno (Czech Republic), 9.-12. June 1999. Faculty of Mechanical Engineering, Brno University of Technology. ga99aZelinka. [1842] Zhengjun Pan, T. Sabisch, R. Adams, and H. Bolouri. Staged training of neocognitron by evolutionary algorithms. In Proceedings of the 1999 Congress on Evolutionary Computation-CEC99, volume 3, pages 1965–1972, Washington, DC, 6.-9. July 1999. IEEE, Piscataway, NJ. †CCA82140/99 ga99aZhengPan. [1843] Ari S. Nissinen, Hannu Koivisto, and Heikki N. Koivo. Optimization of neural network topologies using genetic algorithm. International Journal on Intelligent Automation and Soft Computing, 5(3):211–224, ? 1999. ga99bAriNissinen. [1844] Bernhard Sendhoff. Evolution of Structures - Optimization of artificial neural structures for information processing. Shaker Verkag, ?, 1999. †Wiegand ga99bBSendhoff. [1845] Byoung-Tak Zhang and Je-Gun Joung. Time series prediction using committee machines of evolutionary neural trees. In Proceedings of the 1999 Congress on Evolutionary Computation-CEC99, volume 1, pages 281–186, Washington D.C., 6.-9. July 1999. IEEE, Piscataway, NJ. †CCA82130/99 ga99bByoung-TakZhang. [1846] E. Gómez-Ramı́rez, S. Soltani, A. González-Yunes, and M. Avila-Alvarez. Improving learning process for identification with multiresolution filtering in polynomial artificial neural networks. In ?, editor, IASTED International Conference Intelligent Systems and Control, page ?, Santa Barabara, CA, 28.-30. October 1999. IASTED. (in Spanish as [1765]) ga99bEGomez-Ramirez. [1847] W. Golubski and T. Feuring. Genetic algorithm-based neural-network initializations. In Proceedings of the Computational Intelligence for Modelling, Control & Automation - Neural Networks & Advanced Control Strategies, pages 202–207, Vienna, Austria, 17.-19. February 1999. IOS Press, Amsterdam. †P84321 ga99bGolubski. [1848] Hugo de Garis, M. Korkin, F. Gers, and M. Hough. ATR’s artificial brain (CAM-brain) project: a sample of what idividual CoDi-1Bit model evolved neural net modules can do. In Proceedings of the 1999 Congress on Evolutionary Computation-CEC99, volume 3, pages 1979–1987, Washington D.C., 6.-9. July 1999. IEEE, Piscataway, NJ. †CCA80857/99 ga99bHdeGaris. 164 Genetic algorithms and neural networks [1849] Lin He, Ke-Jun Wang, Hong-Zhong Jin, Guo-Bin Li, and X. Z. Gao. The combination and prospects of neural networks, fuzzy logic and genetic algorithms. In Proceedings of the 1999 IEEE Midnight - Sun Workshop on Soft Computing Methods in Industrial Applications, pages 52–57, Kuusamo, Finland, 16.18. June 1999. IEEE, Piscataway, NJ. †CCA68494/99 ga99bLinHe. [1850] P. Georgilakis, N. Hatziargyriou, D. Paparigas, and J. Bakopoulos. On-line combined use of neural networks and genetic algorithms to the solution of transformer iron loss reduction problem. In International Conference on Electric Power Engineering. PowerTech Budapest 99, volume ?, page 155, Budapest (Hungary), 29. August-2. September 1999. IEEE, Piscataway, NJ. ga99bPGeorgilakis. [1851] R. Kumar. On generalisation of machine learning with neural-evolutionary computations. In Proceedings Third International Conference on Computational Intelligence and Multimedia Applications, pages 112–116, New Delhi, India, 23.-26. September 1999. IEEE Computer Society Press, Los Alamitos , CA. †CCA91974/99 ga99bRKumar. [1852] S. Chen, Y. Wu, and B. L. Luk. Combined genetic algorithm optimization and regularized orthogonal least squares learning for radial basis function networks. IEEE Trans. Neural Netw. (USA), 10(5):1239–1243, 1999. †CCA86492/99 ga99bSChen. [1853] T. Senjyu, A. Miyazato, and K. Uezato. Improvement of power system stability based on adaptive control using genetic algorithm and neural network. Bull. Fac. Eng. Univ. Ryukyus (Japan), (57):117–129, 1999. In Japanese †CCA54762/99 ga99bTSenjyu. [1854] Xin Yao. Evolving artificial neural networks. Proc. IEEE (USA), 87(9):1423–1447, 1999. †CCA77494/99 ga99bXinYao. [1855] Bernhard Sendhoff and Martin Kreutz. A model for the dynamic interaction between evolution and learning. Neural Processing Letters, 10(3):181–193, ? 1999. ga99cBSendhoff. [1856] E. Gómez-Ramı́rez, A. S. Poznyak, and R. Lozano. Adaptive control of nonlinear systems using polynomial artificial neural network. In ?, editor, IASTED International Conference Intelligent Systems and Control, page ?, Santa Barabara, CA, 28.-30. October 1999. IASTED. ga99cEGomez-Ramirez. [1857] Ari S. Nissinen, Heikki Hyötyniemi, and Heikki N. Koivo. Classification of radiation spectra using map of linear classifiers. In ?, editor, Proceedings of the International Conference on Computational Intelligence for Modelling Control and Automation, volume ?, pages 128–133, Vienna (Austria), 17.-19. February 1999. IOS Press BV, Netherlands. ga99dAriNissinen. [1858] E. Gómez-Ramı́rez, A. S. Poznyak, A. González-Yunes, and M. Avila-Alvarez. Adaptive control of nonlinear systems using polynomial artificial neural network. In ?, editor, Congress on Evolutionary Computation CEC99, page ?, Washington, DC, 6.-9. July 1999. IEEE. ga99dEGomez-Ramirez. [1859] Ari S. Nissinen and Heikki Hyötyniemi. Analysis of evolutionary self-organizing map. Technical report 115, Helsinki University of Technology, Control Engineering Laboratory, 1999. ga99eAriNissinen. [1860] Jarmo T. Alander. Indexed bibliography of genetic algorithms and neural networks. Report 94-1-NN, University of Vaasa, Department of Information Technology and Production Economics, 1995. (ftp: //ftp.uwasa.fics/report94-1/gaNNbib.pdf) gaNNbib. [1861] Janne Haverinen. Utilizing the fundamental effect of space in creating purposeful dynamic systems. In Jarmo T. Alander, Pekka Ala-Siuru, and Heikki Hyötyniemi, editors, STeP-2004, Proceedings of the 11th Finnish Artificial Intelligence Conference, volume 3, pages 137–150, Vantaa (Finland), 1.-3. September 2004. Finnish Artificial Intelligence Society (FAIS). (also ) STeP04Haverinen. [1862] T. Goto, H. Ase, M. Yamagishi, Y. Hirota, and S. Fujii. Application of GA, neural network and AI to planning problems. NKK Technical Report (Japan), (144):78–85, 1993. (in Japanese) * CCA 18141/93 ga:Fujii93a. [1863] Jinn-Moon Yang and Cheng-Yan Kao. An evolutionary algorithm to training neural networks for a twospiral problem. pages 1025–1032, 2000. ga00aJ-MYang. [1864] José Rui Ferreira, João A. Peças Lopes, and João Tomé Saraiva. A real time approach to identify actions to prevent voltage collapse using genetic algorithms and neural networks. In IEEE Power Engineering Society Summer Meeting, volume 1, pages 255–260, Seattle, WA, 16.-20. July 2000. IEEE, Piscataway, NJ. ga00aJRFerreira. [1865] M. J. Embrechts, d. Devogelaere, and M. Rijkaert. Supervised scaled regression clustering: an alternative to neural network. In S.-I. Amari, C. L. Giles, M. Gory, and V. Piuri, editors, Proceedings of thr IEEEINNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000, volume 6, pages 571–576, Como, Italy, 24.-27.July 2000. IEEE, Piscataway, NJ. * www/IEEE ga00aMJEmbrechts. Bibliography 165 [1866] Nilay Roy, Walter Potter, and David Landau. Designing polymer blends using neural networks, genetic algorithms, and Markov chains. In ?, editor, American Physical Society, April Meeting, volume ?, page ?, Long Beach, CA, 29. April-2. May 2000. American Physical Society. †NASA ADS ga00aNRoy. [1867] P. K. Dash, S. Mishra, S. Dash, and A. C. Liew. Genetic optimization of a self organizing fuzzy - neural network for load forecasting. In IEEE Power Engineering Society Winter Meeting, volume 2, pages 1011– 1016, Singapore, 23.-27. January 2000. IEEE, Piscataway, NJ. ga00aPKDash. [1868] R. V. Parbhane, S. Unniraman, S. S. Tambe, V. Nagaraja, and B. D. Kulkarni. Optimum DNA curvature using a hybrid approach involving an artificial neural network and genetic algorithm. J. Biomol. Struct. Dyn., 17(4):665–672, February 2000. * PubMed10698104 ga00aRVParbhane. [1869] Zhou Ji, Luo Yingli, Zhang Jianhua, and Cui Xiang. A neural network identifier of synchronous machines trained by object oriented genetic algorithm and back propagation. In IEEE Power Engineering Society Winter Meeting, volume 1, pages 239–242, Singapore, 23.-27. January 2000. IEEE, Piscataway, NJ. ga00aZJi. [1870] Johannes Schemmel, Karlheinz Meier, and Felix Schürmann. A VLSI implementation of an analog neural network suited for genetic algorithms. In Y. Liu, K. Tanaka, M. Iwata, T. Higuchi, and M. Yasunaga, editors, Evolvable Systems: From Biology to Hardware, 4th International Conference, ICES 2001, volume LNCS of 2210, pages 50–61, Tokyo (Japan), 3.-5. October 2001. Springer-Verlag Berlin Heidelberg. * www /Springer ga01aJSchemmel. [1871] Y. H. Lee, B. J. Cahill, S. J. Porter, and A. C. Marvin. In-situ optimization of cost function for genetic algorithm using neural networks applied to antenna design. In Eleventh International Conference on Antennas and Propagation, volume 2 of IEE Conf. Publ. No. 480, pages 456–459, Manchester, UK, 17.20. April 2001. IEEE, Piscataway, NJ. ga01aYHLee. [1872] T. T. Chow, G. Q. Zhang, Z. Lin, and C. L Song. Global optimization of absorption chiller system be genetic algorithm and neural network. Energy and Buildings, 34(1):103–109, January 2002. †www /Elsevier ga02aTTChow. [1873] Yong Zhang, Junhua Liu, Yonghuai Zhang, and Xiaojun Tang. Cross sensitivity reduction of gas sensors using genetic neural network. Optical Engineering, 41(3):615–625, March 2002. * www/SPIE Web ga02aYZhang. [1874] T. M. English. Generalization in populations of recurrent neural networks. In Proceedings of the Third Annual Conference on Evolutionary Programming, pages 26–33, San Diego, CA (USA), 24.-26. February 1994. World Scientific, Singapore. †CCA59145/96 ga94bEnglish. [1875] Janusz Kacprzyk. Fuzzy systems, neural networks and evolutionary programming: new paradigms for decision support. In Proceedings of the 4th International Workshop, Current Issues in Fuzzy Technologies, pages 118–120, Warsaw (Poland), 1.-3. June 1994. Villa Madruzzo, Trento, Italy. † ga94bKacprzyk. [1876] E. Schoneburg. The genetic formula engine. a unified approach for neural network optimisation and multivariate data analysis based on genetic algorithms. In ?, editor, Proceedings of the Adaptive Computing and Information Processing, volume 2, pages 413–426, London, UK, 25.-27. January 1994. Unicom Seminars, Uxbridge, UK. * CCA26597/96 ga94bSchonebu. [1877] N. Kariya, K. Inatsu, K. Okaya, M. Nonaka, and Y. Okano. Intelligent controls in resources processingparameter adjustments by fuzzy expert system, neural network and genetic algorithm. J. Grad. Sch. Fac. Eng. Univ. Tokyo A (Japan), ?(33):50–51, 1995. (In Japanese) †CCA10870/97 ga95aKariya. [1878] Ren-Guo Song, Qi-Zhi Zhang, Mei-Kuang Tseng, and Bao-Jin Zhang. Application of artificial neural networks to the investigation of aging dynamics in 7175 aluminum alloys. Mater Sci Eng C Biomimetic Mater Sens Systmatische Operationsforschung und Statistik, 3(1):39–41, 1995. †EI M016679/95 ga95bRGSong. [1879] Juan Seijas and Jose L. Sanz-Gonzalez. Two spacecraft attitude determination using neural networks and image processing. In Proceedings of the 1st International Conference, volume 2492, pages 985–994, Orlando, FL, 17.-21. April 1995. Society of Photo- Optical Instrumentation Engineers, Bellingham, WA. †A95-44471 ga95bSeijas. [1880] Yong Ho Kim, Seong Hyun Kim, Hong Tae Jeon, and Hong-Gi Lee. On designing a fuzzy-neural network control system combined with genetic algorithm. Journal of Korean Institute of Telematics and Electronics, 32B(8):75–82, 1996. †CCA28774/96 ga96bKim. [1881] Miles F. Jefferson, Neil Pendleton, Sam B. Lucas, and Michael A. Horan. Comparison of a genetic algorithm neural network with logistic regression for predicting outcome after surgery for patients with nonsmall cell lung carcinoma. Cancer Letters, 79(7):1338–1342, 1997. †BAb129197 ga97aJefferso. 166 Genetic algorithms and neural networks [1882] Jin Seon Yeun, Nam Kim, J. K. Pan, R. S. Kim, J. U. Um, and S. H. Kim. Performance evaluation of the GA/SA hybrid heuristic optimum filter for optical pattern recognition. In ?, editor, Proceedings of the Applications of artificial neural networks in image processing II, volume SPIE-, pages 109–114, Bellingham, WA, 12.-13. February 1997. Society of Photo-Optical Instrumentation Engineers, Bellingham, WA. †A97-34783 ga97aJinSeonYeun. [1883] P. A. D. Junior. Air-pollution monitoring using genetic algorithm, fuzzy-logic and neural networks. In Proceedings of the Management and Control of Production and Logistics, volume 1-2, pages 617–620, Cambinas, Brazil, 31. aug- 3. sep ? 1997. Elsevier Science Publ B V, Amsterdam. †P82958 ga97aPAJunior. [1884] V. S. Desai, Daniel G. Conway, J. N. Crook, and G. A. Overstreet. Credit-scoring models in the credit.union environment using neural networks and genetic algorithms. IMA Journal of Mathematics Applied in Business and Industry (UK), 8(4):323–346, 1997. †CCA100049/97 ga97aVSDesai. [1885] S. Hobday, R. Smith, and J. Balbruno. Applications of genetic algorithms and neural networks to interatomic potentials. Nuclear instruments & Methods in Physics Research Section B-Beam Interactions with Materials and Atoms, 153(1-4):247–263, 1998. †P85207 ga98aSHobday. [1886] M. Michael Vai and Sheila Prasad. Applications of neural networks optimized by the genetic algorithm to microwave systems. In IEEE International Symposium on Antennas and Propagation Society, volume 4, pages 2580–2583, Orlando, FL, USA, 11.-16. July 1999. IEEE, Piscataway, NJ. ga99aMMVai. [1887] David B. Fogel. Blondie24: Playing at the Edge of AI. Morgan Kaufmann Publishers, San Francisco, CA, 2001. †GAdigest v15 n39 ga01aDBFogel. [1888] Daniel S. Weile and Eric Michielssen. Genetic algorithm optimization applied to electromagnetics - a review. IEEE Transactions on Antennas and Propagation, 45(3):343–353, March 1997. (89 refs) ga97aWeile. [1889] R. F. Albrecht, C. R. Reeves, and N. C. Steele, editors. Artificial Neural Nets and Genetic Algorithms, Innsbruck, Austria, 13. -16. April 1993. Springer-Verlag, Wien. ga:ANNGA93. [1890] David B. Fogel and J. Wirt Atmar, editors. Proceedings of the 1st Annual Conference on Evolutionary Programming, LaJolla, CA, 21.-22. February 1992. Evolutionary Programming Society, San Diego. † ga:EP92. [1891] R. Männer and B. Manderick, editors. Parallel Problem Solving from Nature, 2, Brussels, 28.-30. September 1992. Elsevier Science Publishers, Amsterdam. ga:PPSN2. [1892] Proceedings of the IEEE Workshop on Genetic Algorithms, Neural Networks and Simulated Annealing applied to problems in signal and image processing, University of Glasgow (UK), ? 1990. IEEE. † ga:GANNSA90. [1893] H. Roitblat, Jean-Arcady Meyer, and Stewart W. Wilson, editors. From Animals to Animats, Proceedings of the Second International Conference on Simulation of Adaptive Behavior (SAB92), Honolulu, HI, 7.11. December 1992. The MIT Press, Cambridge, MA. ga:SAB92. [1894] J. David Schaffer, editor. Proceedings of the Third International Conference on Genetic Algorithms, Georg Mason University, 4.-7. June 1989. Morgan Kaufmann Publishers, Inc. ga:GA3. [1895] Christopher G. Langton, Charles Taylor, J. Doyne Farmer, and Steen Rasmussen, editors. Artificial Life II, Proceedings of the Workshop on Artificial Life Held February, 1990 in Santa Fe, New Mexico, Proceedings Volume X, Santa Fe Institute Studies in the Sciences of Complexity. Addison-Wesley, Reading, MA, 1992. ga:ALifeII. [1896] Hans-Paul Schwefel and R. Männer, editors. Parallel Problem Solving from Nature, volume 496 of Lecture Notes in Computer Science, Dortmund (Germany), 1.-3. October 1991. Springer-Verlag, Berlin. (Proceedings of the 1st Workshop on Parallel Problem Solving from Nature (PPSN1)) ga:PPSN1. [1897] Francisco J. Varela and Paul Bourgine, editors. Toward a Practice of Autonomous System: Proceedings of the First European Conference on Artificial Life, Paris, 11.-13. December 1991. MIT Press, Cambridge, MA. ga:ECAL91. [1898] ?, editor. Self-organization and life, from simple rules to global complexity, Proceedings of the Second European Conference on Artificial Life, Brussels (Belgium), 24.-26. May 1993. MIT Press, Cambridge, MA. ga:ECAL93. [1899] John R. Koza. Genetic Programming: On Programming Computers by Means of Natural Selection and Genetics. The MIT Press, Cambridge, MA, 1992. ga:Koza92book. [1900] Jean-Arcady Meyer and Stewart W. Wilson, editors. Proceedings of the First International Conference on Simulation of Adaptive Behavior: From animals to animats, Paris, 24.-28. September 1991. A Bradford Book, MIT Press, Cambridge, MA. ga:SAB90. Bibliography 167 [1901] Stephanie Forrest, editor. Proceedings of the Fifth International Conference on Genetic Algorithms, Urbana-Champaign, IL, 17.-21. July 1993. Morgan Kaufmann, San Mateo, CA. ga:GA5. [1902] Lawrence Davis, editor. Genetic Algorithms and Simulated Annealing, London, 1987. Pitman Publishing. ga:Davis87book. [1903] Richard K. Belew and Lashon B. Booker, editors. Proceedings of the Fourth International Conference on Genetic Algorithms, San Diego, 13.-16. July 1991. Morgan Kaufmann Publishers. ga:GA4. [1904] Stefan Elfwing. Embodied Evolution of Learning Ability. PhD thesis, Kungliga Tekniska högskolan,Nada, 2007. ga07bSElfwing. [1905] A. V. Sebald and Lawrence J. Fogel, editors. Proceedings of the Fourth Annual Conference on Evolutionary Programming (EP94), San Diego, CA, 24.-26. February 1994. World Scientific, Singapore. †Fogel ga94EP. [1906] Proceedings of the First IEEE Conference on Evolutionary Computation, Orlando, FL, 27.-29. June 1994. IEEE, New York, NY. ga94ICCIEC. [1907] Yuval Davidor, Hans-Paul Schwefel, and Reinhard Manner, editors. Parallel Problem Solving from Nature – PPSN III, volume 866 of Lecture Notes in Computer Science, Jerusalem (Israel), 9.-14. October 1994. Springer-Verlag, Berlin. † ga94PPSN3. [1908] Proceedings of the Second European Congress on Intelligent Techniques and Soft Computing (EUFIT’94), Aachen (Germany), 20.-23. September 1994. ELITE-Foundation. ga94EUFIT. [1909] Proceedings of ICCI94/Neural Networks, Orlando, FL, 26. June - 2. July 1994. IEEE, New York, NY. † ga94ICCINN. [1910] T. Diveux, P. Sebastian, D. Bernard, J. R. Puiggali, and J. Y. Grandidier. Horizontal axis wind turbine systems: optimization using genetic algorithms. Wind Energy, 4(4):151–171, October-December 2001. ga01aTDiveux. [1911] Orazio Miglino, Henrik Hautop Lund, and Stefano Nolfi. Evolving mobile robots in simulated and real environments. Artificial Life, 2(4):417–434, Summer 1995. ga95aMiglino. [1912] Stephen D. Scott, Sharad Seth, and Ashok Samal. A synthesizable VHDL coding of a genetic algorithm. Technical Report UNL-CSE-97-009, University of Nebraska-Lincoln, 1997. ga97aSDScott. [1913] D. W. Pearson, N. C. Steele, and R. F. Albrecht, editors. Artificial Neural Nets and Genetic Algorithms, Alès (France), 19.-21. April 1995. Springer-Verlag, Wien New York. ga95ICANNGA. [1914] Lance D. Chambers, editor. Practical Handbook of Genetic Algorithms, volume 2, Applications. CRC Press, Boca Raton, FL, 1995. ga95CRC2. [1915] Jarmo T. Alander, editor. Proceedings of the First Nordic Workshop on Genetic Algorithms and their Applications (1NWGA), Proceedings of the University of Vaasa, Nro. 2, Vaasa (Finland), 9.-12. January 1995. University of Vaasa. (ftp://ftp.uwasa.fics/1NWGA/*.ps.Z) ga95NWGA. [1916] J. R. McDonnell, R. G. Reynolds, and David B. Fogel, editors. Evolutionary Programming IV: Proceedings of the Fourth Annual Conference on Evolutionary Programming (EP95), San Diego, CA, 1.-3. March 1995. MIT Press. †Fogel ga95EP. [1917] Proceedings of the Second IEEE Conference on Evolutionary Computation, Perth (Australia), November 1995. IEEE, New York, NY. ga95ICEC. [1918] Proceedings of the First IEE/IEEE International Conference on Genetic Algorithms in Engineering Systems: Innovations and Applications, Sheffield (UK), 12.-14. September 1995. IEEE. †conf. prog. ga95Sheffield. [1919] Pavel Ošmera, editor. Proceedings of the MENDEL’95, Brno (Czech Republic), 26.-28. September 1995. Technical University of Brno. ga95Brno. [1920] The Korea Science Engineering Foundation, The Australian Academy of Science, The Australian Academy of Technological Sciences and Engineering. Proceedings of the 1st Korea - Australia Joint Workshop on Evolutionary Computation, Taejon (Korea), 26.-29. September 1995. KAIST, Korea. ga95Korea-Australia. [1921] Larry J. Eshelman, editor. Proceedings of the Sixth International Conference on Genetic Algorithms, Pittsburgh, PA, 15.-19. July 1995. ? †prog ga95ICGA. [1922] Ian Parmee and M. J. Denham, editors. Adaptive Computing in Engineering Design and Control ’96 (ACEDC’96), 2nd International Conference of the Integration of Genetic Algorithms and Neural Network Computing and Related Adaptive Techniques with Current Engineering Practice, Plymouth (UK), 26.28. March 1996. ? (to appear) †conf.prog. ga96Plymouth. 168 Genetic algorithms and neural networks [1923] Hans-Michael Voigt, Werner Ebeling, Ingo Rechenberg, and Hans-Paul Schwefel, editors. Parallel Problem Solving from Nature – PPSN IV, volume 1141 of Lecture Notes in Computer Science, Berlin (Germany), 22.-26. September 1996. Springer-Verlag, Berlin. ga96PPSN4. [1924] Sankar K. Pal and Paul P. Wang, editors. Genetic Algorithms for Pattern Recognition. CRC Press, Boca Raton, FL, 1996. †www.amazon.com GAdigest v 10 n 28 ga96aSKPal. [1925] John R. Koza, David E. Goldberg, David B. Fogel, and Rick L. Riolo, editors. Proceedings of the GP-96 Conference, Stanford, CA, 28.-31. July 1996. MIT Press, Cambridge, MA. †prog ga96GP. [1926] Jarmo T. Alander, editor. Proceedings of the Second Nordic Workshop on Genetic Algorithms and their Applications (2NWGA), Proceedings of the University of Vaasa, Nro. 11, Vaasa (Finland), 19.-23. August 1996. University of Vaasa. (ftp://ftp.uwasa.fics/2NWGA/*.ps.Z) ga96NWGA. [1927] Pavel Ošmera, editor. Proceedings of the MENDEL’96, Brno (Czech Republic), June 1996. Technical University of Brno. ga96Brno. [1928] In ?, editor, Proceedings of the Artificial Evolution 97 (EA’97) Conference, Nimes (France), 22.-24. October 1997. Springer-Verlag, Berlin. †prog ga97EA. [1929] John R. Koza, Kalyanmoy Deb, Marco Dorico, David B. Fogel, Max Garson, Hitoshi Iba, and Rick L. Riolo, editors. Genetic Programming 1997: Proceedings of the Second Annual Conference, Stanford, CA, 13.-16. July 1997. Morgan Kaufmann, San Francisco, CA. †prog ga97GP. [1930] Jarmo T. Alander, editor. Proceedings of the Third Nordic Workshop on Genetic Algorithms and their Applications (3NWGA), Helsinki (Finland), 18.-22. August 1997. Finnish Artificial Intelligence Society (FAIS). (ftp://ftp.uwasa.fics/3NWGA/*.ps.Z) ga97NWGA. [1931] Michael Blumenstein, editor. Proceedings of the International Conference on Computational Intelligence and Multimedia Applications, Gold Coast, QUE, Australia, February 1997. Watson Ferguson & Company (Griffith University). †toc /Blumenstein ga97ICCIMA. [1932] Witold Pedrycz, editor. Fuzzy Evolutionary Computation. Kluwer Academic Publishers, New York, 1997. ga97aPedrycz. [1933] Pavel Ošmera, editor. Proceedings of the 3rd International Mendel Conference on Genetic Algorithms, Optimization problems, Fuzzy Logic, Neural networks, Rough Sets (MENDEL’97), Brno (Czech Republic), 25.-27. June 1997. Technical University of Brno. ga97Brno. [1934] Pavel Ošmera, editor. Proceedings of the 4th International Mendel Conference on Genetic Algorithms, Optimization problems, Fuzzy Logic, Neural networks, Rough Sets (MENDEL’98), Brno (Czech Republic), 24.-26. June 1998. Technical University of Brno. ga98Brno. [1935] Sankar K. Pal, Ashish Ghosh, and Malay K. Kundu. Soft computing and image analysis: features, relevance and hybridization. pages 1–20. 2000. ga00bSankarKPal. [1936] Javier Causa, Gorazd Karer, Alfredo N´ ñez, Doris Sáez, Igor Škrjanc, and Borut Zupančič. Hybrid fuzzy predictive control based on genetic algorithms for the temperature control of a batch reactor. Computers and Chemical Engineering, 32(?):3254– 3263, ? 2008. ga08aJavierCausa. [1937] K. C. Tan, T. H. Lee, and E. F. Khor. Evolutionary algorithms with dynamic population size and local exploration for multiobjective optimization. IEEE Transactions on Evolutionary Computation, 5(6):565– 588, December 2001. ga01aKCTan. Notations †(ref) = the bibliography item does not belong to my collection of genetic papers. (ref) = citation source code. ACM = ACM Guide to Computing Literature, EEA = Electrical & Electronics Abstracts, BA = Biological Abstracts, CCA = Computers & Control Abstracts, CTI = Current Technology Index, EI = The Engineering Index (A = Annual, M = Monthly), DAI = Dissertation Abstracts International, P = Index to Scientific & Technical Proceedings, PA = Physics Abstracts, PubMed = National Library of Medicine, BackBib = Thomas Bäck’s unpublished bibliography, Fogel/Bib = David Fogel’s EA bibliography, etc * = only abstract seen. ? = data of this field is missing (BiBTeX-format). The last field in each reference item in Teletype font is the BiBTEXkey of the corresponding reference. University of Vaasa, Finland 169 170 Genetic algorithms and neural networks Appendix A Bibliography entry formats This documentation was prepared with LATEX and reproduced from camera-ready copy supplied by the editor. The ones who are familiar with BibTeX may have noticed that the references are printed using abbrv bibliography style and have no difficulties in interpreting the entries. For those not so familiar with BibTeX are given the following formats of the most common entry types. The optional fields are enclosed by ”[ ]” in the format description. Unknown fields are shown by ”?”. † after the entry means that neither the article nor the abstract of the article was available for reviewing and so the reference entry and/or its indexing may be more or less incomplete. Book: Author(s), Title, Publisher, Publisher’s address, year. Example John H. Holland. Adaptation in Natural and Artificial Systems. The University of Michigan Press, Ann Arbor, 1975. Journal article: Author(s), Title, Journal, volume(number): first page – last page, [month,] year. Example David E. Goldberg. Computer-aided gas pipeline operation using genetic algorithms and rule learning. Part I: Genetic algorithms in pipeline optimization. Engineering with Computers, 3(?):35–45, 1987. †. Note: the number of the journal unknown, the article has not been seen. Proceedings article: Author(s), Title, editor(s) of the proceedings, Title of Proceedings, [volume,] pages, location of the conference, date of the conference, publisher of the proceedings, publisher’s address. Example John R. Koza. Hierarchical genetic algorithms operating on populations of computer programs. In N. S. Sridharan, editor, Eleventh International Joint Conference on Artificial Intelligence (IJCAI-89), pages 768–774, Detroit, MI, 20.-25. August 1989. Morgan Kaufmann, Palo Alto, CA. † . Technical report: Author(s), Title, type and number, institute, year. Example Thomas Bäck, Frank Hoffmeister, and Hans-Paul Schwefel. Applications of evolutionary algorithms. Technical Report SYS-2/92, University of Dortmund, Department of Computer Science, 1992. 171 172 Vaasa GA Bibliography Vaasa GA Bibliography 173 Vaasa Genetic Algorithm Bibliography Search & Optimise Main features: • Over 20,000 references to published papers • by over 20,000 researchers. • Available as over 70 special bibliographies online: http://lipas.uwasa.fi/~TAU/reports/report94-1/ga*bib.pdf files. • Covers all sciences and engineering fields, from basic theory to applications. • Several indexes and statistical summaries. • See what problems evolution can solve for you! Global optimisation and search heuristics called genetic algorithm mimics evolution in nature using recombination and selection from a set of solution trials called population. One of the most prominent attractive features of genetic algorithms from the practical point of view of software techniques is their simplicity, which makes them easy to implement and tailor to solve practical search and optimisation problems. In spite of the seemingly simple processing, the genetic algorithms are good at solving some problems that are known to be hard. The simplicity, generality, flexibility, parallelism, and the good problem solving capability have made genetic algorithm very popular among various disciplines desperately searching methods to solve difficult optimisation problems. ————— Observe that our server has also a selection of our papers on genetic algorithms and other compuational topics. See our bibliographies or file ftp.uwasa.fi/cs/README for further details. 174 file ga90bib.ps.Z . . . ga02bib.ps.Z gaACOUSTICSbib.pdf gaAIbib.pdf gaAERObib.pdf gaAGRObib.pdf gaALIFEbib.pdf gaARTbib.pdf gaAUSbib.pdf gaBASICSbib.pdf gaBIObib.pdf gaCADbib.pdf gaCHEMbib.pdf gaCHEMPHYSbib.ps.Z gaCIVILbib.pdf gaCODEbib.pdf gaCOEVObib.pdf gaCONTROLbib.pdf gaCSbib.pdf gaEARLYbib.pdf gaEAST-EURObib.ps.Z gaECObib.pdf gaECOLbib.pdf gaELMAbib.pdf gaESbib.pdf gaFAR-EASTbib.ps.Z gaFEMbib.pdf gaFPGAbib.pdf gaFRAbib.ps.Z gaFTPbib.ps.Z gaFUZZYbib.pdf gaGEObib.pdf gaGERbib.ps.Z gaGPbib.pdf gaIMPLEbib.pdf gaINDIAbib.ps.Z gaINVERSEbib.pdf gaIREGbib.pdf gaISbib.pdf gaJAPANbib.ps.Z gaLCSbib.pdf gaLASERbib.pdf gaLATINbib.ps.Z gaLOGISTICSbib.pdf gaMANUbib.pdf gaMATHbib.pdf gaMEDICINEbib.pdf gaMEDITERbib.ps.Z gaMICRObib.pdf gaMILbib.pdf gaMLbib.pdf gaMSEbib.pdf gaNANObib.pdf gaNIRbib.pdf gaNNbib.pdf gaNORDICbib.pdf gaOPTICSbib.pdf gaOPTIMIbib.pdf gaORbib.pdf Vaasa GA Bibliography # refs . .. updated . .. 557 190 2402 854 359 181 170 659 1040 1358 1346 938 2277 1068 377 232 1875 1453 723 679 1569 170 568 464 1556 86 333 540 1353 1476 436 1586 971 1419 276 291 180 87 2404 211 58 649 689 2009/01/07 2008/03/20 2008/09/18 2012/02/29 2008/03/20 2008/03/12 2003/07/09 2012/02/29 2011/07/07 2010/03/05 2008/08/13 2011/12/29 2009/07/24 2012/06/28 2011/12/29 2003/07/09 2009/08/17 2011/12/28 2004/09/22 2008/08/13 2009/08/17 2003/05/23 2010/01/08 2010/04/15 2009/08/17 2008/05/22 2008/08/13 2009/07/31 2003/07/09 2009/07/27 846 704 1810 83 113 897 490 109 194 1883 1039 2055 923 1689 2009/07/27 2012/03/22 2003/07/09 2008/03/31 2009/08/17 2007/11/02 2008/06/11 2008/04/07 2009/07/27 2012/06/28 2012/06/28 2011/07/07 2003/07/09 2011/07/05 2009/08/17 2007/11/01 2009/01/07 2010/04/09 2009/07/24 2010/08/12 2008/05/22 2008/08/13 2008/08/11 2009/07/24 2009/07/24 ...table continues on the next page... contents GA in 1990 . .. GA in 2002 GA in acoustics (new: March 2008) GA in artificial intelligence GA in aerospace GA in agriculture (new) GA in artificial life GA in art and music GA in Australia and New Zealand Basics of GA GA in biosciences including medicine GA in Computer Aided Design GA in chemical sciences ; previously in gaCHEMPHYSbib.ps.Z GA in chemistry and physics; divided into gaCHEMbib.ps.Z and gaPHYSbib.ps.Z 2002 GA in civil, structural, and mechanical engineering GA coding co- and differential evolution GA(new) GA in control and process engineering GA in comp. sci. (incl. databases, /mining, software testing and GP) GA in yearly yeas (upto 1989) new GA in the Eastern Europe GA in economics and finance GA in ecology and biodiversity (new: 1.8.2008) GA in electromagnetics Evolution strategies GA in the Far East (excl. Japan) GA & FEM (new May 2008) GA & FPGA (new May 2008) GA in France GA papers available via web (ftp and www) GA and fuzzy logic GA in geosciences GA in Germany, Austria, and Switzerland genetic programming implementations of GA GA in India GA in inverse problems (new: Aug 2007) image registration (new: July 2009) immune systems GA in Japan Learning Classifier Systems GA and lasers (new: April 2008) GA in Latin America, Portugal & Spain GA in logistics (incl. TSP) GA in manufacturing GA in mathematics GA in medicine (new: Nov 2007) GA in the Mediterranean GA in microscopy & microsystems (new: March 2008) GA in military applications GA in machine learning new GA in materials new GA in nanotechnology new GA in NIRS (spectroscopy) new GA in neural networks GA in Nordic countries GA in optics and image processing GA and optimization (only a few refs) GA in operations research Vaasa GA Bibliography file gaPARAbib.pdf gaPARETObib.pdf gaPATENTbib.pdf gaPATTERNbib.pdf gaPHYSbib.pdf gaPIEZObib.pdf gaPOWERbib.pdf gaPROTEINbib.pdf gaQCbib.pdf gaREMOTEbib.pdf gaROBOTbib.pdf gaSAbib.pdf gaSCHEDULINGbib.pdf gaSELECTIONbib.ps.Z gaSIGNALbib.pdf gaSIMULAbib.pdf gaTELEbib.pdf gaTHEORYbib.pdf gaTHESESbib.pdf gaVAASAbib.pdf gaVLSIbib.pdf gaUKbib.ps.Z gaXbib.ps.Z X-rays new: October 2010 # refs 828 469 462 1528 2313 54 976 491 547 300 775 331 862 295 2403 1037 840 2483 578 284 883 1998 123 175 updated 2011/12/23 2009/03/24 2009/07/27 2007/11/06 2008/04/07 2009/08/17 2012/06/28 2008/03/12 2011/03/09 2011/12/29 2009/07/27 2009/07/24 2011/12/29 2009/07/27 2009/07/31 2009/07/24 2009/07/27 2008/08/13 2009/01/07 2010/08/17 2011/12/28 2008/05/22 2010/10/22 contents Parallel and distributed GA Pareto optimization GA patents GA in pattern recognition incl. LCS (new) GA in physical sciences ; previously in gaCHEMPHYSbib.ps.Z GA & piezo (new: March 2008) GA in power engineering GA in protein research quantum computing GA in remote sensing (new: 1.8.2008) GA in robotics GA and simulated annealing GA in scheduling Selection in GAs (new) GA in signal and image processing GA in simulation GA in telecom Theory and analysis of GA PhD etc theses GA in Vaasa (new: August 2010) GA in electronics, VLSI design and testing GA in United Kingdom GA Table A.1: Indexed genetic algorithm special bibliographies available online in directory http://lipas.uwasa.fi/~TAU/reports/report94-1. New updates only as .pdf files.